Reactive performance monitoring of Cloud computing environments

Mdhaffar, Afef; Halima, Riadh Ben; Jmaïel, Mohamed; Freisleben, Bernd

doi:10.1007/s10586-016-0676-4

Cited by 7 publications

(4 citation statements)

References 16 publications

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“…CEP is a technique for realtime, fast processing of a large number of events from an event stream to derive some complex events and to identify important patterns in the event stream. CEP has found its applications in a variety of business domains such as retail management, health-care, and cloud computing [15,12]. The basic or primitive events in CEP are processed into complex or composite events by means of event processing queries, analysis rules, and patterns, which are written in a Structured Query Language (SQL)-like language.…”

Section: Cep and Collision Predictionmentioning

confidence: 99%

Towards a realtime, collision-free motion coordination and navigation system for a UAV fleet

Ashraf

Majd

Troubitsynå

2017

Proceedings of the Fifth European Conference on the Engineering of Computer-Based Systems

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This paper presents a realtime, collision-free motion coordination and navigation system for an Unmanned Aerial Vehicle (UAV) fleet. The proposed system uses geographical locations of the UAVs and of the successfully detected, static and moving obstacles to predict and avoid: (1) UAVto-UAV collisions, (2) UAV-to-static-obstacle collisions, and (3) UAV-tomoving-obstacle collisions. Our collision prediction approach leverages efficient runtime monitoring and Complex Event Processing (CEP) to make timely predictions. A distinctive feature of the proposed system is its ability to foresee a risk of a collision in realtime and proactively find best ways to avoid the predicted collisions in order to ensure safety of the entire fleet. We also present a simulation-based implementation of the proposed system along with an experimental evaluation involving a series of experiments. The results demonstrate that the proposed system successfully predicts and avoids all three kinds of collisions in realtime. Moreover, it generates efficient UAV routes, has an excellent runtime performance, efficiently scales to large-sized problem instances involving dozens of UAVs and obstacles, and is suitable for some densely populated, cluttered flying zones.

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Section: Cep and Collision Predictionmentioning

confidence: 99%

Towards a realtime, collision-free motion coordination and navigation system for a UAV fleet

Ashraf

Majd

Troubitsynå

2017

Proceedings of the Fifth European Conference on the Engineering of Computer-Based Systems

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“…Complex Event Processing (CEP) is a technique for realtime, fast processing of a large number of events from one or more event streams to derive and identify important complex events and patterns in the event streams. CEP has been successfully used in a variety of business domains including retail management, health-care, and cloud computing [20,26]. For example in retail management, CEP can be used to detect shoplifting and out-of-stock events.…”

Section: Complex Event Processing and Collision Predictionmentioning

confidence: 99%

Online Path Generation and Navigation for Swarms of UAVs

Ashraf

Majd

Troubitsynå

2020

Scientific Programming

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With the growing popularity of Unmanned Aerial Vehicles (UAVs) for consumer applications, the number of accidents involving UAVs is also increasing rapidly. Therefore, motion safety of UAVs has become a prime concern for UAV operators. For a swarm of UAVs, a safe operation can not be guaranteed without preventing the UAVs from colliding with one another and with static and dynamically appearing, moving obstacles in the flying zone. In this paper, we present an online, collision-free path generation and navigation system for swarms of UAVs. The proposed system uses geographical locations of the UAVs and of the successfully detected, static and moving obstacles to predict and avoid: (1) UAV-to-UAV collisions, (2) UAV-to-static-obstacle collisions, and (3) UAV-tomoving-obstacle collisions. Our collision prediction approach leverages efficient runtime monitoring and Complex Event Processing (CEP) to make timely predictions. A distinctive feature of the proposed system is its ability to foresee potential collisions and proactively find best ways to avoid predicted collisions in order to ensure safety of the entire swarm. We also present a simulation-based implementation of the proposed system along with an experimental evaluation involving a series of experiments and compare our results with the results of four existing approaches. The results show that the proposed system successfully predicts and avoids all three kinds of collisions in an online manner. Moreover, it generates safe and efficient UAV routes, efficiently scales to large-sized problem instances, and is suitable for cluttered flying zones and for scenarios involving high risks of UAV collisions.

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“…Mdhaffar et al has studied cloud monitoring in several studies –. Saleh et al has introduced yet another cloud monitoring tool that can facilitate autoscaling IaaS clouds .…”

Section: Literature Reviewmentioning

confidence: 99%

“…Mdhaffar et al has studied cloud monitoring in several studies. [6][7][8][9] Saleh et al has introduced yet another cloud monitoring tool that can facilitate autoscaling IaaS clouds. 10 We differ from these studies as they focus on solutions that are dependent on the implementation of the cloud computing platforms that they are incorporated.…”

Section: Literature Reviewmentioning

confidence: 99%

Hybrid cloud computing monitoring software architecture

Aktaş

2018

Concurrency and Computation

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Summary Cloud computing provides scalable computing resources on demand. Monitoring cloud computing resources is important so that resources can be dynamically allocated, migrated, or shut down to meet users' requirements. Challenges in cloud computing monitoring systems include detecting patterns that might lead to failure of the cloud system, detecting malfunctioning problems within the cloud platform after they occur, and issues related to the fact that existing monitoring solutions are tightly coupled to specific cloud platforms, while there is an emerging need for monitoring solutions that are independent of underlying subsystems. To address these challenges, we designed a hybrid cloud monitoring software architecture that can work as an add‐on layer on top of existing cloud computing platforms. The proposed architecture is designed based on facade software design pattern and utilizes complex event processing concept in which data from various primitive metrics streams is processed to detect previously defined patterns. Prototype applications have been developed to demonstrate the architecture's usability. Performance tests were applied to prototype applications. Computation times required for the operation of the proposed architecture were negligible.

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Reactive performance monitoring of Cloud computing environments

Cited by 7 publications

References 16 publications

Towards a realtime, collision-free motion coordination and navigation system for a UAV fleet

Towards a realtime, collision-free motion coordination and navigation system for a UAV fleet

Online Path Generation and Navigation for Swarms of UAVs

Hybrid cloud computing monitoring software architecture

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