Software-Defined Cloud Computing: A Systematic Review on Latest Trends and Developments

Abbasi, Aaqif Afzaal; Abbasi, Almas; Shamshirband, Shahaboddin; Chronopoulos, Anthony T.; Persico, Valerio; Pescapè, Antonio

doi:10.1109/access.2019.2927822

Cited by 59 publications

(29 citation statements)

References 134 publications

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“…More importantly, most of the traditional modeling approaches rely on queuing theory and its related methods [5]. Queuing-based control methods are most suitable for steady-state systems, where the system properties do not change with time, but these are not fit for dynamic systems, such as in datacenter traffic engineering.…”

Section: Introductionmentioning

confidence: 99%

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Bouncer: A Resource-Aware Admission Control Scheme for Cloud Services

et al. 2019

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Cloud computing is a paradigm that ensures the flexible, convenient and on-demand provisioning of a shared pool of configurable network and computing resources. Its services can be offered by either private or public infrastructures, depending on who owns the operational infrastructure. Much research has been conducted to improve a cloud’s resource provisioning techniques. Unfortunately, sometimes an abrupt increase in the demand for cloud services results in resource shortages affecting both providers and consumers. This uncertainty of resource demands by users can lead to catastrophic failures of cloud systems, thus reducing the number of accepted service requests. In this paper, we present Bouncer—a workload admission control scheme for cloud services. Bouncer works by ensuring that cloud services do not exceed the cloud infrastructure’s threshold capacity. By adopting an application-aware approach, we implemented Bouncer on software-defined network (SDN) infrastructure. Furthermore, we conduct an extensive study to evaluate our framework’s performance. Our evaluation shows that Bouncer significantly outperforms the conventional service admission control schemes, which are still state of the art.

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Section: Introductionmentioning

confidence: 99%

“…We then consider another queue "j", containing available VMs. In order to address the utility maximization concerns for queue structures [5], we ensure that every incoming application is provided with its required resource demands. Total response time Wt (Qinprogress) Waiting time of in-process requests of cluster Q Wt (Qwaiting)…”

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confidence: 99%

Bouncer: A Resource-Aware Admission Control Scheme for Cloud Services

et al. 2019

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“…Abbasi et al studied software-defined cloud computing (SDCC) and explained its main architectural components. Additionally, there are numerous opportunities and possible threats of SDCC in applications [21]. Ubale and Jain introduced various SDN vulnerabilities and various DDoS attack methods.…”

Section: Related Workmentioning

confidence: 99%

Counteracting UDP Flooding Attacks in SDN

Wei

Tung

2020

Electronics

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Software-defined networking (SDN) is a new networking architecture with a centralized control mechanism. SDN has proven to be successful in improving not only the network performance, but also security. However, centralized control in the SDN architecture is associated with new security vulnerabilities. In particular, user-datagram-protocol (UDP) flooding attacks can be easily launched and cause serious packet-transmission delays, controller-performance loss, and even network shutdown. In response to applications in the Internet of Things (IoT) field, this study considers UDP flooding attacks in SDN and proposes two lightweight countermeasures. The first method sometimes sacrifices address-resolution-protocol (ARP) requests to achieve a high level of security. In the second method, although packets must sometimes be sacrificed when undergoing an attack before starting to defend, the detection of the network state can prevent normal packets from being sacrificed. When blocking a network attack, attacks from the affected port are directly blocked without affecting normal ports. The performance and security of the proposed methods were confirmed by means of extensive experiments. Compared with the situation where no defense is implemented, or similar defense methods are implemented, after simulating a UDP flooding attack, our proposed method performed better in terms of the available bandwidth, central-processing-unit (CPU) consumption, and network delay time.

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“…Bhaskarwar, et al [12] studied and focused on control system implementation of heat exchangers of the type of shell and tube through a number of tools such as PLC, Supervisory Control and Data Acquisition SCADA, Lab VIEW and the Internet. The above efforts and works can serve and support the smart grid technology that basically consists of smart meters, sensors, proper monitoring and data management system [13] [14][15] [16]. The point of the present proposed system in this paper, related to the above selected papers, is most of the work done before, SMS has been used to monitor and control the home appliances, transformer and single cable.…”

Section: Introductionmentioning

confidence: 99%

Monitoring and Controlling Electric Power Stations Using GSM Network

Ismail

Mubdir

Majeed

et al. 2019

KJAR

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This paper introduces a system design for monitoring and controls the components of power generation station and substation with help of existing communication link based on GSM network. In this design, a selected Programmable Logic Controller (PLC) connected to the fields that needed to be monitored and continuously read changes in measurements of electrical parameters like voltage, current, bus bar circuit breakers…..etc.. These parameters have been monitored by PLC, on the base of conditions that PLC is programmed. PLC generates a text message and forward to other side; control center or mobile phone of engineer and technicians; who are responsible of monitoring. At control center, another GSM modem which has capability to connect with personal computer, receives that text massage using SMS and executes it. Software written with Vb.Net, works as Human Machine Interface (HMI) for this purpose. The system performance is acceptable in terms of errors in readings and time delay. The percentage error for the current is about 1%, and for the voltage is about 0.2%. The delivery time to receive new analog and digital inputs data is about 14.125 seconds, while the control of the circuit done after 4.68 seconds.

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Software-Defined Cloud Computing: A Systematic Review on Latest Trends and Developments

Cited by 59 publications

References 134 publications

Bouncer: A Resource-Aware Admission Control Scheme for Cloud Services

Bouncer: A Resource-Aware Admission Control Scheme for Cloud Services

Counteracting UDP Flooding Attacks in SDN

Monitoring and Controlling Electric Power Stations Using GSM Network

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