Optimizing web server RAM performance using birth–death process queuing system: scalable memory issue

Salmanian, Zolfaghar; Izadkhah, Habib; Isazadeh, Ayaz

doi:10.1007/s11227-017-2081-z

Cited by 3 publications

(1 citation statement)

References 20 publications

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“…Outrun. According to Little's law [78], under steady-state conditions, the average number of items in a queuing system equals the average rate at which items arrive multiplied by the average time that an item spends in the system. Let us consider a queuing process where L is number of users, transactions, processes, etc.…”

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confidence: 99%

Tackling Verification and Validation Techniques to Evaluate Cyber Situational Awareness Capabilities

Sánchez

Rodríguez-Bermejo²,

Medenou³

et al. 2022

Mathematics

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Since cyberspace was identified as a domain of operations, defence practitioners started a race with academy, researchers, and industry and military organizations working together towards defining related lines of capability development (e.g., DOTMLPFI) and exploring the needs and opportunities they entail. An essential cornerstone of adapting to the convergence of the cyber domain with conventional theaters of operation is the need for producing tools for easing to acquire cyber situational awareness (CSA), from which human operators shall be able to perceive, reason and project situations and events observed in cyberspace that may vertically/horizontally propagate from technological to tactical, operational and strategic planes. Benefiting from the higher maturity level of civilian capabilities for cybersecurity, the military sector has embraced the challenge of creating related beyond state-of-the-art CSA enablers that comprise the existing technological background while adopting concepts such as operations, missions or courses of action (CoAs), properly aligning them with military doctrine. Beyond ongoing development efforts, there is a wide methodological gap in the lack of suitable CSA verification and validation (V&V) frameworks, which are expected to analyze if related capabilities meet the requirements to operate in the military context; at the same time supporting the thorough development life-cycle of brand new cyber defence technologies. With the motivation of closing the identified gap, this research introduces a novel V&V framework able to guide the evaluation of CSA-related tools, which makes converge purely military aspects with dual-use state-of-the-art V&V approaches. Three core CSA evaluation concepts are discussed in-depth: software, operational and application tests. They range from the daily application of new capabilities to their ability to enable the acquisition of a joint operational picture understandable by human decision makers.

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mentioning

confidence: 99%

Tackling Verification and Validation Techniques to Evaluate Cyber Situational Awareness Capabilities

Sánchez

Rodríguez-Bermejo²,

Medenou³

et al. 2022

Mathematics

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Auto-Scale Resource Provisioning In IaaS Clouds

Salmanian

Izadkhah

Isazadeh

2020

The Computer Journal

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Users of cloud computing technology can lease resources instead of spending an excessive charge for their ownership. For service delivery in the infrastructure-as-a-service model of the cloud computing paradigm, virtual machines (VMs) are created by the hypervisor. This software is installed on a bare-metal server, called the host, and acted as a broker between the hardware of the host and its VMs. The host is responsible for the allocation of required resources, such as CPU, RAM and network bandwidth, for VMs. Therefore, allocating resources to a VM is equivalent to finding the location of the VM on the hosts. In this paper, we propose a model for resource allocation of a datacenter that includes clusters of hosts. This model is based on the birth–death process of queueing systems and continuous-time Markov chains. We will focus on RAM-intensive VMs and consider the allocation of RAM for a VM as a job in the queueing systems. The purpose of this modeling is to keep the number of running hosts minimum while guaranteeing the quality of service in terms of response. When the utilization of active hosts reaches a predefined threshold value, a new host is added to prevent response time violation, and when host utilization is reduced to a certain threshold, one of the hosts can be deactivated. The experimental results show that, in the long run, the odds of working with more jobs are increased.

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