A cloud middleware for assuring performance and high availability of soft real-time applications

Cloud Computing (CC) is becoming increasingly pertinent and popular. A natural consequence of this is that many modern-day data centers experience very high internal traffic within the data centers themselves. The VMs with high mutual traffic often end up being far apart in the data center network, forcing them to communicate over unnecessarily long distances. The consequent traffic bottlenecks negatively affect both the performance of the application and the network in its entirety, posing non-trivial challenges for the administrators of these cloud- based data centers. The problem can, quite naturally, be compartmentalized into two phases which follow each other. First of all, the VMs are consolidated with a VM clustering algorithm, and this is achieved by utilizing the toolbox involving Learning Automata (LA). By mapping the clustering problem onto the Graph Partitioning (GP) problem, our LA-based solution successfully reduces the total communication cost by amounts that range between 34% to 85%. Thereafter, the resulting clusters are assigned to the server racks using a cluster placement algorithm that involves a completely different intelligent strategy, i.e., one that invokes Simulated Annealing (SA). This phase further reduces the total cost of communication by amounts that range between 89% to 99%. The analysis and results for different models and topologies demonstrate that the optimization is done in a fast and computationally-efficient way. Indeed, as far as we know, this paper pioneers the application of LA in the traffic-aware consolidation of virtual machines in data centers, and also pioneers a strategy which serializes the tools in LA and SA to optimize CC.

In this work, we focus on the problem of virtual machines (VMs) placement in geographically distributed data centers. We consider communicating VMs assigned to data centers that are connected over an IP-over-WDM network. We aim to plan and optimize the placement of VMs in data centers so as to minimize the IP-traffic within the backbone network. Thus, we propose first, a formulation which can be considered as a variant of the Hub Location problem modeling and we show its extreme difficulty for medium and large size instances. In order to overcome this difficulty, we reformulate the problem by multi-commodity flow, adopt variable aggregating methods and add valid inequalities to strengthen this new formulation. The different experiments that we present show the effectiveness of our last model in terms of running time and computational resources.

The financial services sector demands high availability and security due to its critical role in global economies and the sensitive nature of its data. Active/active data center strategies have emerged as a robust solution, enabling continuous operations even during outages or maintenance by ensuring that all data centers are fully operational and synchronized. This paper explores the benefits and challenges of implementing active/active data centers in financial services, focusing on the intricate balance between achieving high availability and maintaining rigorous security standards. Active/active configurations provide unparalleled redundancy and uptime, crucial for minimizing service disruptions that could lead to significant financial losses or reputational damage. By distributing workloads across multiple active data centers, financial institutions can enhance resilience against localized failures and ensure seamless failover capabilities. However, this high availability comes with complex challenges, particularly in ensuring that security protocols are uniformly applied across all active sites. The risk of data breaches and cyberattacks increases as more endpoints are exposed, making it essential to implement advanced security measures, such as end-to-end encryption, real-time threat detection, and stringent access controls. The review also discusses the importance of regulatory compliance, as financial institutions must navigate a landscape of diverse and often stringent regulations across different jurisdictions. Achieving a balance between high availability and security requires not only technological innovation but also strategic planning and ongoing risk assessment. Emerging trends in cloud computing and software-defined networking (SDN) are also considered, highlighting how these technologies can support the dynamic and secure operation of active/active data centers. Ultimately, this review underscores the need for financial institutions to adopt a holistic approach that integrates high availability with robust security frameworks, ensuring that their data centers can meet the demands of a rapidly evolving digital environment while safeguarding against potential threats. Keywords: Security, Financial Services, Data Center, Balancing High Availability, Active.

Cloud computing controls the increasing energy consumption of applications by consolidating them in shared servers through virtualization. This technique can be greatly improved and complemented by choosing an optimal data center for each Virtual Machine (VM). That dynamic optimization problem was stated as a Mixed Integer Linear Programming (MILP) model that minimizes operational expenditures, while respecting constraints on Quality of Service (QoS), power consumption, and CO2 emissions. Geographically distributed users experience varying response times depending on where users and VMs are located. Users closer to VMs experience a shorter response time, thus distributing VMs close to users improves the QoS. On the other hand, the increasing energy consumption of the cloud raised concerns about the impact on CO2 emissions and global warming. Placing VMs in data centers that use green energy sources is an important way to mitigate this problem. A comprehensive optimization modelling framework and an efficient tabu search heuristic were developed to handle applications with dynamic demands in real time. Test cases had more than 1,000 nodes, 650 applications, and 6,500 VMs. Results report that the communication delay is reduced up to 6 times, 30% of power consumption is saved, and the CO2 emissions can be reduced up to 60 times. The framework also allows to carefully assess the trade-offs between delay, cost, CO2 emissions and power consumption.

Stochastic scheduling for variation-aware virtual machine placement in a cloud computing CPS

Transactions can simplify distributed applications by hiding data distribution, concurrency, and failures from the application developer. Ideally the developer would see the abstraction of a single large machine that runs transactions sequentially and never fails. This requires the transactional subsystem to provide opacity (strict serializability for both committed and aborted transactions), as well as transparent fault tolerance with high availability. As even the best abstractions are unlikely to be used if they perform poorly, the system must also provide high performance. Existing distributed transactional designs either weaken this abstraction or are not designed for the best performance within a data center. This paper extends the design of FaRM - which provides strict serializability only for committed transactions - to provide opacity while maintaining FaRM's high throughput, low latency, and high availability within a modern data center. It uses timestamp ordering based on real time with clocks synchronized to within tens of microseconds across a cluster, and a failover protocol to ensure correctness across clock master failures. FaRM with opacity can commit 5.4 million neworder transactions per second when running the TPC-C transaction mix on 90 machines with 3-way replication.

There is an important class of applications in data centre called online dataintensive (OLDI) application, such as search engine, electronic shopping, and advertising, which has low latency, high throughput, and high burstiness. For better user experience, the query response delay in the data centre is controlled under 300 milliseconds. DCTCP can better meet the requirements of OLDI, but all the switches in the data centre are required to support RED. For data centre that does not fully support RED switch, TCP protocol can only be used. TCP Incast will appear in the application, which is far from the requirements of OLDI application. This paper proposes the TCP protocol of data centre based on window control. It is in existing switches and network devices,and centralized control makes the send window match with the switch queue cache. In the case of ensuring low latency, it keeps the switch queue in a small range of fluctuation, enabling the data centre to meet low latency, high throughput and high burstiness application requirements. Simulation experiments verify that WCTCP congestion control method can effectively solve the above problems. It is 5 times lower than TCPNewReno packet loss rate, 6 times higher than the network utilization rate, and the network performance is close to the DCTCP protocol.

Replication is one of the key techniques used in distributed systems to improve high data availability, data access performance and data reliability. To optimize the maximum benefits from file replication, a systems that includes replicas need a strategy for selecting and accessing suitable replicas. A replica selection strategy determines the available replicas and chooses the most access files. In most of these access frequency based solutions or popularity of files are assuming that files are independent of each other. In contrast, distributed systems such as peer-to-peer file sharing, and mobile database, files may be dependent or correlated to one another. Thus, this paper focused on the combination of popularity and affinity files as the most important parameters in selecting replicas in distributed environments. Herein, a replica selection is proposed focusing on popular files and affinity files. The idea is to improve data availability in distributed data replica selection strategy. A P2P simulator, PeerSim, is used to evaluate the performance of the dynamic replica selection strategy. The simulation results provided a proof that the proposed affinity replica selection has contributed towards a new dimension of replica selection strategy that incorporates the affinity and popularity of file replicas in distributed systems.

As the infrastructure of cloud computing and big data, data centers have been deployed widely. Then, how to make full use of the computing and storage resources in data centers will be the focus. Data center networks are considered important solution for the problem above, which include intra-data center and inter-data center networks. Both of them will depend on the optical networking due to its advantages, such as high bandwidth, low latency, and low energy consumption. Data center interconnected by flexi-grid optical networks is a promising scenario to allocate spectral resources for applications in a dynamic, tunable and efficient control manner. Compared with inter-data center, optical interconnect in intra-data center networks is a more pressing need and promising scenario to accommodate these applications in a dynamic, flexible and efficient manner. OpenFlow based Software Defined Networking (SDN) is considered as a good technology, which is very suitable for data center networks. This paper mainly focuses on the data center optical networks based on software defined networking (SDN), which can control the heterogeneous networks with unified resource interface. Architecture and experimental demonstration of OpenFlow-based optical interconnects in intra-data center Networks and OpenFlow-based flexi-grid optical networks for inter-data center are presented in the paper respectively. Some future works are listed finally.

In order to minimize user perceived latency while ensuring high data availability, cloud applications desire to select servers from one of the multiple data centers (i.e., server clusters) in different geographical locations, which are able to provide desired services with low latency and low cost. This paper presents CloudGPS, a new server selection scheme of the cloud computing environment that achieves high scalability and ISP-friendliness. CloudGPS proposes a configurable global performance function that allows Internet service providers (ISPs) and cloud service providers (CSPs) to leverage the cost in terms of inter-domain transit traffic and the quality of service in terms of network latency. CloudGPS bounds the overall burden to be linear with the number of end users. Moreover, compared with traditional approaches, CloudGPS significantly reduces network distance measurement cost (i.e., from O(N) to O(1) for each end user in an application using N data centers). Furthermore, CloudGPS achieves ISP-friendliness by significantly decreasing inter-domain transit traffic.

In the fifth-generation communication system, secured and reliable data packets will rely on the network with high availability and low latency. The 5G network enables the dynamic control of nodes with low latency. Ultra-reliability is one of the challenging tasks in software-defined networks. The ultra-reliability feature is an interface working with high availability and low latency that brings in fifth-generation networks. The Internet of Things will work in the societies so that it required ultra-reliability features to empower the peoples as well as machines for collaborating with their neSoftware Defined Networksighbors. The connections among ultra-reliability networks are extremely hard situations to keep low packets corruption. The Software Defined Networks (SDN) will provide a platform for measuring, controlling, monitoring and scaling the smart objects in reality or virtually. Virtualization enables IT, specialists, to combine or separate the considerable networking or create new programmable networking among virtual machines. In this article, the authors are reviewed the architecture of SDN based on virtualization under the umbrella of 5G networks.

Bandwidth hungry applications such as real-time video processing are currently straining data center networking infrastructure. This is expected to become a more serious challenge in the near future. Optics enables massive data transmission rates: in telecom settings researchers have demonstrated rates in excess of 100 Tb/s in a single mode fiber; however, the data center presents a different set of challenges. Low cost, low power dissipation, low latency, small physical size, and the ability to integrate with mainstream silicon electronics are more important than the ability to transmit signals over long distances, the traditional telecoms focus. A clearer understanding of the requirements and technology challenges of the new applications which are changing the face of the Internet and the data center, should facilitate development of optical interconnection networks that will solve these challenges. By linking the end-to-end research areas we seek to identify critical technology gaps and enable the design of forward-looking, efficient, cost-effective, higher bandwidth data centers that can take optimal advantage of advances in multicore processors.KeywordsCloud ComputingData CenterInterconnection NetworkHigh BandwidthRing ResonatorThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The exponential increase of Internet traffic due to cloud computing and other emerging web applications has created the need for more powerful data centres. These warehouse-scale data centres consist of thousands of racks interconnected with commodity switches and consume vast amount of energy. To face the requirements of the future data centres, new interconnection schemes have to be adopted to provide high throughput and reduced power consumption. Several optical interconnects for future data centre networks have recently appeared that provide high throughput, low latency and reduced power consumption. This paper discusses the need for a shift of the data centres networks to the optical domain to reduce the power consumption and meet the bandwidth requirements. Additionally, this paper presents some indicative optical interconnects for high performance data centres that have appeared recently in the research literature. Finally, it presents a qualitative categorization and comparison of these schemes based on their main features such as performance, connectivity and scalability.

Spectrum engineering in flexible grid data center optical networks

Recent work has presented hierarchical deployment of energy storage devices (ESDs) at the data center, rack, and server levels within a data center, along with a corresponding control framework for peak power shaving and energy cost reduction under (time-of-use) dynamic energy pricing policies. However, the prior work does not use a realistic power delivery architecture of the data center with hierarchical ESD structure, and fails to account for some key characteristics such as rate capacity effect of batteries and power losses in various AC/DC and DC/DC converters in the power delivery architecture. This paper aims to overcome these shortcomings by (i) adopting a realistic power delivery architecture (from Intel) for centralized ESD structure as the starting point, (ii) presenting a novel power delivery architecture for data centers with hierarchical ESD structure, borrowing the best features of the centralized ESD structure from Intel and the distributed single-level ESD structures from Google and Microsoft, (iii) providing a mathematical framework for the optimal design (i.e., ESD provisioning) and control (i.e., Scheduling the charging and discharging of various ESDs) of the hierarchical ESD structure to minimize overall energy cost under dynamic energy pricing functions. This framework accounts for constraints on ESD volume (for each level) and the overall (annually amortized) capital cost, and power losses due to the rate capacity effect and conversion circuitry. The ESD design problem is solved by using a search-based algorithm, whereas the ESD control problem is formulated and solved as a hierarchical convex optimization algorithm. Experiments have been conducted using real Google cluster workload based on realistic data center specifications, demonstrating the effectiveness of the proposed optimal design and control framework.