Performance of Network and Service Monitoring Frameworks

The efficiency and the performance of anagement systems is becoming a hot research topic within the networks and services management community. This concern is due to the new challenges of large scale managed systems, where the management plane is integrated within the functional plane and where management activities have to carry accurate and up-to-date information. We defined a set of primary and secondary metrics to measure the performance of a management approach. Secondary metrics are derived from the primary ones and quantifies mainly the efficiency, the scalability and the impact of management activities. To validate our proposals, we have designed and developed a benchmarking platform dedicated to the measurement of the performance of a JMX manager-agent based management system. The second part of our work deals with the collection of measurement data sets from our JMX benchmarking platform. We mainly studied the effect of both load and the number of agents on the scalability, the impact of management activities on the user perceived performance of a managed server and the delays of JMX operations when carrying variables values. Our findings show that most of these delays follow a Weibull statistical distribution. We used this statistical model to study the behavior of a monitoring algorithm proposed in the literature, under heavy tail delays distribution. In this case, the view of the managed system on the manager side becomes noisy and out of date

Управление устранением неисправностей в ИТ-системах

This article is dedicated to the problems of increasing of efficiency of fault search and elimination in IT-systems. Methods of threshold values determination for the three-threshold scheme are proposed and analyzed. Method of fault localization in IT-systems that incorporates passive symptom gathering and active probing is proposed. Fault management system which uses these methods was developed.Статья посвящена проблемам повышения эффективности поиска и устранения неисправностей в ИТ-системах. Предложены и проанализированы способы определения значений пороговых величин для трехпороговой схемы принятия решений. Предложен метод локализации неисправностей в ИТ-системах, объединяющий использование пассивного сбора симптомов и активных проверок. Разработана структура подсистемы управления устранением неисправностей, реализующая предложенные методы

A Tree-based protocol for enforcing quotas in clouds

Services are increasingly being hosted on cloud nodes to enhance their performance and increase their availability. The virtually unlimited availability of cloud resources enables service owners to consume resources without quantitative restrictions, paying only for what they use. To avoid cost overruns, resource consumption must be controlled and capped when necessary. We present a distributed tree-based protocol for managing quotas in clouds that minimizes communication overheads and reduces the time required to determine whether a quota has been exhausted. Experimental evaluation shows that our protocol reduces communication costs by 42% relative to a distributed baseline solution and is up to 15 times faster

Adaptive monitoring: A systematic mapping

Context: Adaptive monitoring is a method used in a variety of domains for responding to changing conditions. It has been applied in different ways, from monitoring systems’ customization to re-composition, in different application domains. However, to the best of our knowledge, there are no studies analyzing how adaptive monitoring differs or resembles among the existing approaches. Objective: To characterize the current state of the art on adaptive monitoring, specifically to: (a) identify the main concepts in the adaptive monitoring topic; (b) determine the demographic characteristics of the studies published in this topic; (c) identify how adaptive monitoring is conducted and evaluated by the different approaches; (d) identify patterns in the approaches supporting adaptive monitoring. Method: We have conducted a systematic mapping study of adaptive monitoring approaches following recommended practices. We have applied automatic search and snowballing sampling on different sources and used rigorous selection criteria to retrieve the final set of papers. Moreover, we have used an existing qualitative analysis method for extracting relevant data from studies. Finally, we have applied data mining techniques for identifying patterns in the solutions. Results: We have evaluated 110 studies organized in 81 approaches that support adaptive monitoring. By analyzing them, we have: (1) surveyed related terms and definitions of adaptive monitoring and proposed a generic one; (2) visualized studies’ demographic data and arranged the studies into approaches; (3) characterized the main approaches’ contributions; (4) determined how approaches conduct the adaptation process and evaluate their solutions. Conclusions This cross-domain overview of the current state of the art on adaptive monitoring may be a solid and comprehensive baseline for researchers and practitioners in the field. Especially, it may help in identifying opportunities of research; for instance, the need of proposing generic and flexible software engineering solutions for supporting adaptive monitoring in a variety of systems.Peer ReviewedPostprint (author's final draft

Leveraging Reinforcement Learning for Adaptive Monitoring of Low-Power IoT Networks

International audienceLow-power Internet of Things (IoT) networks are widely deployed in various environments with resource constrained devices, making their states monitoring particularly challenging. In this paper, we propose an adaptive monitoring mechanism for low-power IoT devices, by using a reinforcement learning (RL) method to automatically adapt the polling frequencies of the collected attributes. Our goal is to minimize the number of monitoring packets while keeping accurate and timely detection of threshold crossings associated to supervised attributes. We study the various RL parameter settings under different monitoring attribute behaviors using OpenAi Gym simulator. We implement the RL based adaptive polling in Contiki OS and we evaluate its performance using Cooja simulator. Our results show that our approach converges to optimal polling frequencies and outperforms static periodic notification-based methods by reducing the number of monitoring packets, with a percentage of correctly detected threshold crossings exceeding 80%

Improving SNI-based HTTPS Security Monitoring

International audienceRecent surveys show that the proportion of encrypted web traffic is quickly increasing. On one side, it provides users with essential properties of security and privacy, but on the other side, it raises important challenges and issues for organizations, related to the security monitoring of encrypted traffic (filtering, anomaly detection, etc.). This paper proposes to improve a recent technique for HTTPS traffic monitoring that is based on the Server Name Indication (SNI) field of TLS and which has been implemented in many firewall solutions. This method currently has some weaknesses that can be used to bypass firewalls by overwriting the SNI value of new TLS connections. Our investigation shows that 92% of the HTTPS websites surveyed in this paper can be accessed with a fake SNI. Our approach verifies the coherence between the real destination server and the claimed value of SNI by relying on a trusted DNS service. Experimental results show the ability to overcome the shortage of SNI-based monitoring by detecting forged SNI values while having a very small false positive rate (1.7%). The overhead of our solution only adds negligible delays to access HTTPS websites. The proposed method opens the door to improve global HTTPS monitoring and firewall systems

Efficient Distributed Monitoring in 6LoWPAN Networks

International audienceMonitoring constrained, low power and lossy networks is essential to many operations including troubleshooting, forensics, performance management. The main challenge for the monitoring plane in these networks is to efficiently cope with both frequently changing topologies and constrained resources. We present a novel algorithm and the supporting framework that improves a poller-pollee based architecture. We empower the poller-pollee placement decision process and operation by exploiting available routing data to monitor nodes status. In addition, monitoring data is efficiently embedded in any messages flowing through the network, drastically reducing monitoring overhead. Our approach is validated through both simulation, implementation and deployment on a 6LoWPAN-enabled network. Results demonstrate that our approach is less aggressive and less resource consuming than its competitors