1. |
- Dürango, Jonas, et al.
(author)
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A control theoretical approach to non-intrusive geo-replication for cloud services
- 2016
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In: 2016 IEEE 55TH CONFERENCE ON DECISION AND CONTROL (CDC). - : IEEE. - 9781509018376 ; , s. 1649-1656
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Conference paper (peer-reviewed)abstract
- Complete data center failures may occur due to disastrous events such as earthquakes or fires. To attain robustness against such failures and reduce the probability of data loss, data must be replicated in another data center sufficiently geographically separated from the original data center. Implementing geo-replication is expensive as every data update operation in the original data center must be replicated in the backup. Running the application and the replication service in parallel is cost effective but creates a trade-off between potential replication consistency and data loss and reduced application performance due to network resource contention. We model this trade-off and provide a control-theoretical solution based on Model Predictive Control to dynamically allocate network bandwidth to accommodate the objectives of both replication and application data streams. We evaluate our control solution through simulations emulating the individual services, their traffic flows, and the shared network resource. The MPC solution is able to maintain a consistent performance over periods of persistent overload, and is quickly able to indiscriminately recover once the system return to a stable state. Additionally, the MPC balances the two objectives of consistency and performance according to the proportions specified in the objective function.
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2. |
- Höst, Stefan, et al.
(author)
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Network Requirements for Latency-Critical Services in a Full Cloud Deployment
- 2016
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In: SoftCom 2016.
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Conference paper (peer-reviewed)abstract
- The end-point of the cloud trend is that all compu- tational and storage resources leave the homes and move to the cloud. We can be rather certain the future eventually looks like this as IT and telecommunications services are commoditised and the end users’ time, interest and skill to acquire and maintain electronics fade away. The network architecture suitable for such scenario will be analysed in terms of latency critical services to establish delay requirements and feasible localisations of the data centers. It is concluded that for cloud gaming as an example of a time-critical service, the maximum delay is limited to 20 ms. In the network architecture this corresponds to locating the data center in the Main CO, i.e. typically in the aggregation part of a metropolitan network.
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3. |
- Li, Zheng, et al.
(author)
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Using a Predator-Prey Model to Explain Variations of Cloud Spot Price
- 2016
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In: Proceedings of the 6th International Conference on Cloud Computing and Services Science (CLOSER 2016). ; , s. 1-8
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Conference paper (peer-reviewed)abstract
- The spot pricing scheme has been considered to be resource-efficient for providers and cost-effective for consumers in the Cloud market. Nevertheless, unlike the static and straightforward strategies of trading on-demand and reserved Cloud services, the market-driven mechanism for trading spot service would be complicated for both implementation and understanding. The largely invisible market activities and their complex interactions could especially make Cloud consumers hesitate to enter the spot market. To reduce the complexity in understanding the Cloud spot market, we decided to reveal the backend information behind spot price variations. Inspired by the methodology of reverse engineering, we developed a Predator-Prey model that can simulate the interactions between demand and resource based on the visible spot price traces. The simulation results have shown some basic regular patterns of market activities with respect to Amazon’s spot instance type m3.large. Although the findings of this study need further validation by using practical data, our work essentially suggests a promising approach (i.e. using a Predator-Prey model) to investigate spot market activities.
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5. |
- Mehta, Amardeep, 1985-, et al.
(author)
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How beneficial are intermediate layer Data Centers in Mobile Edge Networks?
- 2016
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In: Workshops on Fog and Mobile Edge Computing at Foundations and Applications of Self* Systems. - 9781509036516 ; , s. 222-229
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Conference paper (peer-reviewed)abstract
- To reduce the congestion due to the future bandwidth- hungry applications in domains such as Health care, Internet of Things (IoT), etc., we study the benefit of introducing additional Data Centers (DCs) closer to the network edge for the optimal application placement. Our study shows that the edge layer DCs in a Mobile Edge Network (MEN) infrastructure is cost beneficial for the bandwidth-hungry applications having their strong demand locality and in the scenarios where large capacity is deployed at the edge layer DCs. The cost savings for such applications can go up to 67%. Additional intermediate layer DCs close to the root DC can be marginally cost beneficial for the compute intensive applications with medium or low demand locality. Hence, a Telecom Network Operator should start building an edge DC first having capacity up to hundreds of servers at the network edge to cater the emerging bandwidth- hungry applications and to minimize its operational cost.
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6. |
- Tärneberg, William, et al.
(author)
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Experiences Creating a Framework for Smart Traffic Control using AWS IOT
- 2016
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In: UCC'16 : Proceedings of the 9th International Conference on Utility and Cloud Computing - Proceedings of the 9th International Conference on Utility and Cloud Computing. - New York, NY, USA : ACM. - 9781450346160 ; , s. 63-69
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Conference paper (peer-reviewed)abstract
- Public clouds such as Amazon Web Services (AWS) and Microsoft’s Azure provide excellent capabilities for scalable Web applications and Hadoop-based processing. Recent ad- ditions to public clouds to support connected devices and IoT have the potential to similarly disrupt emerging home- grown and/or proprietary approaches. While early public cloud IoT success stories have focused on smaller-scale sce- narios such as connected houses, it is unclear to what ex- tent these new public cloud mechanisms and abstractions are suitable and effective for larger-scale and/or scientific scenarios, which often have a different set of constraints or requirements. In this paper, the design and implementa- tion of a representative cloud-based IoT infrastructure in a specific public cloud – AWS – is presented. The system created is for dynamic vehicle traffic control based on vehi- cle volumes/patterns and public transport punctuality. We find that constructing server-less, stateful, and data driven IoT applications in AWS that can operate in real-time is non-trivial. The primary challenges span application man- ageability and design, latency performance, asynchronicity, and scalability.
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