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Kusnanto Yudhi - One of the best experts on this subject based on the ideXlab platform.
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ANALISIS KERENTANAN DAN KEHANDALAN LAYANAN JARINGAN Cloud BERBASIS PLATFORM EUCALYPTUS
'Universitas Sriwijaya - Pusat Inovasi Pembelajaran Unsri', 2016Co-Authors: Kusnanto YudhiAbstract:Abstract Cloud computing is a computing paradigm that evolves from existing technology, such as grid computing, virtualization and the Internet. Cloud computing provides an illusion of unlimited computing resources, which can be accessed from anywhere, anytime. Despite the potential gains achieved from the Cloud computing, the model security is still questionable which hindered adoption. The security problem becomes more complicated under the Cloud model as new dimensions have entered into the problem scope related to the model architecture, multi-tenancy, elasticity, and layers dependency stack. Eucalyptus-based Cloud network services widely deployed as private Cloud infrastructure. Experiment on this paper focused on finding potential denial-of-service (DOS) and the impact on ability to provide services during attack. We observe an increase on response time up to 2863.22% during attack to the web-based management service. Reducing average system load to an acceptable level, help prevents disruption of the service, by implementing rate control and rate limit on Cloud Controller. Keywords: Cloud computing, network security, operating system, Eucalyptus  Abstrak Cloud computing adalah sebuah teknologi yang mampu memberi ilusi sumber daya komputasi yang tak terhingga, yang dapat diakses dari mana saja, kapan saja. Meskipun Cloud computing berpotensi memberikan manfaat yang besar, namun masalah keamanannya masih menjadi pertanyaan, yang mana menghambat adopsi-nya. Persoalan keamanan pada Cloud computing menjadi semakin rumit karena karakteristik Cloud computing yang khas seperti kelenturan alokasi sumber daya, dan pengguna yang jamak. Jaringan Cloud berbasis platform Eucalyptus banyak diterapkan pada fasilitas Cloud privat. Penelitian ini bertujuan untuk mengetahui potensi hambatan atas pelayanan jaringan Cloud akibat serangan yang terarah (targeted attack), pada sistem jaringan Cloud berbasis platform Eucalyptus. Pengujian menunjukkan adanya peningkatan waktu respons hingga 2863,22% akibat serangan terarah terhadap layanan web administrasi. Penerapan pembatasan dan kendali laju data (rate control, rate limit) pada penelitian ini merupakan solusi untuk mengurangi dampak serangan terarah. Dengan langkah mitigasi ini peningkatan beban dapat dikendalikan sehingga tidak memengaruhi pelayanan. Pengujian kerentanan menunjukkan layanan jaringan Cloud berbasis platform Eucalyptus tidak memiliki ancaman kerentanan yang berpotensi menjadi serangan keamanan. Kata kunci: Cloud computing; keamanan jaringan, sistem operasi, Eucalyptu
Kusnanto Y. - One of the best experts on this subject based on the ideXlab platform.
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Analisis Kerentanan Dan Kehandalan Layanan Jaringan Cloud Berbasis Platform Eucalyptus
'Faculty of Computer Science Sriwijaya University', 2016Co-Authors: Kusnanto Y.Abstract:Cloud computing is a computing paradigm that evolves from existing technology, such as grid computing, virtualization and the Internet. Cloud computing provides an illusion of unlimited computing resources, which can be accessed from anywhere, anytime. Despite the potential gains achieved from the Cloud computing, the model security is still questionable which hindered adoption. The security problem becomes more complicated under the Cloud model as new dimensions have entered into the problem scope related to the model architecture, multi-tenancy, elasticity, and layers dependency stack. Eucalyptus-based Cloud network services widely deployed as private Cloud infrastructure. Experiment on this paper focused on finding potential denial-of-service (DOS) and the impact on ability to provide services during attack. We observe an increase on response time up to 2863.22% during attack to the web-based management service. Reducing average system load to an acceptable level, help prevents disruption of the service, by implementing rate control and rate limit on Cloud Controller
Albert Y Zomaya - One of the best experts on this subject based on the ideXlab platform.
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stackelberg game for energy aware resource allocation to sustain data centers using res
IEEE Transactions on Cloud Computing, 2019Co-Authors: Gagangeet Singh Aujla, Mukesh Singh, Neeraj Kumar, Albert Y ZomayaAbstract:Smart Grid (SG) has emerged as one of the most powerful technologies of the modern era for an efficient energy management by integrating information and communication technologies (ICT) in the existing infrastructure. Among various ICT, Cloud computing (CC) has emerged as one of the leading service providers which uses geo-distributed data centers (DCs) to serve the requests of users in SG. In recent times, with an increase in service requests by end users for various resources, there has been an exponential increase in the number of servers deployed at various DCs. With an increase in the size, the energy consumption of DCs has increased many folds which leads to an increase in overall operational cost of DCs. However, efficient resource allocation among these geo-distributed DCs may play a vital role in reducing the energy consumption of DCs. Moreover, with an increase in harmful emissions, the use of renewable energy sources (RES) can benefit DCs, SG, and society at large. Keeping focus on these points, in this paper, an energy-aware resource allocation scheme is proposed using a Stackelberg game for energy management in Cloud-based DCs. For this purpose, a Cloud Controller is used to receive the requests of users which then distributes these requests among geo-distributed DCs in such a way that the energy consumption of DCs is sustained by RES. However, if energy consumption of DCs is not sustained by RES then the energy is drawn from the grid. The requests of users are routed to the DC which is offered lowest energy tariff from the grid. For this purpose, a Stackelberg game for energy trading is also proposed to select the grid offering lowest energy tariff to DCs. The proposed scheme is evaluated using various performance metrics using Google workload traces. The results obtained show the effectiveness of the proposed scheme.
Erik Elmroth - One of the best experts on this subject based on the ideXlab platform.
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a hybrid Cloud Controller for vertical memory elasticity
Future Generation Computer Systems, 2016Co-Authors: Soodeh Farokhi, Ewnetu Bayuh Lakew, Ivona Brandic, Pooyan Jamshidi, Erik ElmrothAbstract:Web-facing applications are expected to provide certain performance guarantees despite dynamic and continuous workload changes. As a result, application owners are using Cloud computing as it offers the ability to dynamically provision computing resources (e.g., memory, CPU) in response to changes in workload demands to meet performance targets and eliminates upfront costs. Horizontal, vertical, and the combination of the two are the possible dimensions that Cloud application can be scaled in terms of the allocated resources. In vertical elasticity as the focus of this work, the size of virtual machines (VMs) can be adjusted in terms of allocated computing resources according to the runtime workload. A commonly used vertical resource elasticity approach is realized by deciding based on resource utilization, named capacity-based. While a new trend is to use the application performance as a decision making criterion, and such an approach is named performance-based. This paper discusses these two approaches and proposes a novel hybrid elasticity approach that takes into account both the application performance and the resource utilization to leverage the benefits of both approaches. The proposed approach is used in realizing vertical elasticity of memory (named as vertical memory elasticity), where the allocated memory of the VM is auto-scaled at runtime. To this aim, we use control theory to synthesize a feedback Controller that meets the application performance constraints by auto-scaling the allocated memory, i.e., applying vertical memory elasticity. Different from the existing vertical resource elasticity approaches, the novelty of our work lies in utilizing both the memory utilization and application response time as decision making criteria. To verify the resource efficiency and the ability of the Controller in handling unexpected workloads, we have implemented the Controller on top of the Xen hypervisor and performed a series of experiments using the RUBBoS interactive benchmark application, under synthetic and real workloads including Wikipedia and FIFA. The results reveal that the hybrid Controller meets the application performance target with better performance stability (i.e., lower standard deviation of response time), while achieving a high memory utilization (close to 83%), and allocating less memory compared to all other baseline Controllers. A feedback Controller for vertically scale the memory of Cloud applications is proposed.The Controller is able to tune the memory in order to meet the desired performance.The application performance and memory utilization are used as decision making criteria.The feedback Controller guarantees the stability of the Cloud application.The results show the efficiency in memory usage when the feedback Controller is used.
Gagangeet Singh Aujla - One of the best experts on this subject based on the ideXlab platform.
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stackelberg game for energy aware resource allocation to sustain data centers using res
IEEE Transactions on Cloud Computing, 2019Co-Authors: Gagangeet Singh Aujla, Mukesh Singh, Neeraj Kumar, Albert Y ZomayaAbstract:Smart Grid (SG) has emerged as one of the most powerful technologies of the modern era for an efficient energy management by integrating information and communication technologies (ICT) in the existing infrastructure. Among various ICT, Cloud computing (CC) has emerged as one of the leading service providers which uses geo-distributed data centers (DCs) to serve the requests of users in SG. In recent times, with an increase in service requests by end users for various resources, there has been an exponential increase in the number of servers deployed at various DCs. With an increase in the size, the energy consumption of DCs has increased many folds which leads to an increase in overall operational cost of DCs. However, efficient resource allocation among these geo-distributed DCs may play a vital role in reducing the energy consumption of DCs. Moreover, with an increase in harmful emissions, the use of renewable energy sources (RES) can benefit DCs, SG, and society at large. Keeping focus on these points, in this paper, an energy-aware resource allocation scheme is proposed using a Stackelberg game for energy management in Cloud-based DCs. For this purpose, a Cloud Controller is used to receive the requests of users which then distributes these requests among geo-distributed DCs in such a way that the energy consumption of DCs is sustained by RES. However, if energy consumption of DCs is not sustained by RES then the energy is drawn from the grid. The requests of users are routed to the DC which is offered lowest energy tariff from the grid. For this purpose, a Stackelberg game for energy trading is also proposed to select the grid offering lowest energy tariff to DCs. The proposed scheme is evaluated using various performance metrics using Google workload traces. The results obtained show the effectiveness of the proposed scheme.