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Volcano monitoring systems by using Wireless Sensor Networks (WSN) must ensure an adequate network performance, which — in fact — depends on the number of network nodes. This paper is focused on determining the number of nodes, which collectively are able to yield an adequate network performance. We implemented function optimization methods and QoS metric analysis to find the effective number of sensors...
As more knowledge is vastly added to the devices fuelling the Internet of Things (IoT) energy efficiency and real-time data processing are great challenges that must be tackled. In this paper, we introduce ADMin, a low-cost IoT framework that reduces on device energy consumption and the volume of data disseminated across the network. This is achieved by efficiently adapting the rate at which IoT devices...
Infrastructure-as-a-Service environments are becoming increasingly popular. When there is a failure, many applications require service restoration within a few seconds. Reaction to failures in Cloud is still slow for many applications. Monitoring is limited to instance metrics that are not conducive to precise diagnosis due to complexity of virtualization in physical hosts. Interferences among different...
Over the past decade, numerous systems have been proposed to detect and subsequently prevent or mitigate security vulnerabilities. However, many existing intrusion or anomaly detection solutions are limited to a subset of the traffic due to scalability issues, hence failing to operate at line-rate on large, high-speed datacentre networks. In this paper, we present a two-level solution for anomaly...
Applications employing data classification such as smart lighting that involve human factors such as perception lead to non-deterministic input-output relationships where more than one output may be acceptable for a given input. For these so called non-deterministic multiple output classification (nDMOC) problems, the relationship between the input and output may change over time making it difficult...
The combination of fast online anomaly detection and offline learning is a vital element of operations in large-scale datacenters and utility clouds. Given ever-increasing datacenter sizes coupled with the complexities of systems software, applications, and workload patterns, such anomaly detection must operate continuous and real-time at runtime. Further, detection should function for both hardware...
The main target of 5G network technologies is to offer radically increased user capacity and quality of service, while saving energy and reducing investment and operating costs. A key technology in this pursue is the cloudification of the virtualized network functions, which can eventually create an environment where services for network operators and application / content providers are chained, configured,...
Recently, the significance of data mining and machine learning have been highlighted in diversified application scenarios. Various data mining and machine learning techniques are often used to analyze the gigantic amount of data to create more commercial values in high-end enterprise systems. However, the advancement of technologies has made data mining and machine learning possible on low-end systems,...
Citizens develop Wireless Mesh Networks (WMN) in many areas as an alternative or their only way for local interconnection and access to the Internet. This access is often achieved through the use of several shared web proxy gateways. These network infrastructures consist of heterogeneous technologies and combine diverse routing protocols. Network-aware state-of-art proxy selection schemes for WMNs...
The Domain Name Service (DNS) is a vital service in the Internet. Much more than a simple translation mechanism, it also allows higher profile functionalities such as load balancing and enhanced content distribution. In the scope of cloud computing, DNS is foreseen as an elastic and robust service, supporting failover mechanisms, decentralised configuration and multi-tenant isolation.
Top-k reports are compound metrics that provide useful information when diagnosing problems in a system, e.g., to identify persistent CPU usage by a process. In large systems, these reports are collected at regular intervals and need to be resampled to a coarser granularity to answer user queries for different sampling periods, or to save space and make it possible to keep historical data for long...
Odour concentration is measured sensorially, thus needing a human panel, whereas the measurement of odorous compounds is typically based on physical and chemical analysis. Some systems such as electronic noses try to correlate both approaches in order to measure odour instrumentally, which would allow monitoring odour continuously. In the domain of instrumental odour monitoring, e-noses are the main...
With cloud computing consolidation, Platform-as-a-Service (PaaS) has been used as a solution for developing applications with low cost and maximum flexibility. However, an open challenge related to PaaS is the proper handling of multi-tier and stateful applications with support for high availability (HA); and scalability can be considered an essential feature for HA. However, dealing with several...
In conventional large-scale networks, creation and management of network services are costly and complex tasks that often consume a lot of resources, including time and manpower. Network softwarization and network function virtualization have been introduced to tackle these problems, aiming at decreasing costs and complexity of implementing new services, maintaining the implemented services, and managing...
Performance monitoring is essential for all subsystems, especially high performance computing systems. These systems are sensitive to errors and failures which lead to data losses and then severely impact on the organizations. Consequently, resource information in the systems (e.g., CPU usage, memory usage, disk I/O usage, etc.) during the operations must be collected through the system monitoring...
5G mobile communication systems will need to accommodate a variety of use-cases, resulting in a diverse set of requirements. To meet these requirements, 5G systems take advantage of modern virtualization possibilities offered by Network Function Virtualization (NFV), enabling deployment agility and dynamicity of virtualized network functions. With the transformation of telecom towards virtualized...
For a successful and efficient network supervision, an Anomaly Detection System is essential. In this paper, our goal is to develop a simple, practical, and application-domain specific approach to identify anomalies in the input/output data of network probes. Since data are periodic and continuously evolving, it is not possible to use threshold-based approaches. We propose an algorithm based on pattern...
AMNESiA is an affinity measurement platform for NFV-enabled networks, designed to consolidate and interpret existing monitoring data into an affinity metric, aiding operators to identify affinity and anti-affinity relations in the network. AMNESiA uses the latest snapshot of usage data, collected through a generic monitoring solution, from the database to measure affinity between VNFs.
Anecdotes, news reports, and policy briefings collectively suggest that Internet censorship practices are pervasive. The scale and diversity of Internet censorship practices makes it difficult to precisely monitor where, when, and how censorship occurs, as well as what is censored. The potential risks in performing the measurements make this problem even more challenging. As a result, many accounts...
The Dynamic Spectrum Management is a key to increase the spectrum efficiency usage in rapidly growing demand for spectrum in military operations. In the paper, the main results of national project concerning DSM proposals for Polish Armed Forces are presented.
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