Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges

Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.Comment: 12 pages, 5 figures,Proceedings of the 2010 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA 2010), Las Vegas, USA, July 12-15, 201

A Survey on Secure Storage Services in Cloud Computing

Cloud computing is an emerging technology and it is purely based on internet and its environment It provides different services to users such as Software-as-a-Service SaaS PaaS IaaS Storage-as-a-service SaaS Using Storage-as-a-Service users and organizations can store their data remotely which poses new security risks towards the correctness of data in cloud In order to achieve secure cloud storage there exists different techniques such as flexible distributed storage integrity auditing mechanism distributed erasure-coded data Merkle Hash Tree MHT construction etc These techniques support secure and efficient dynamic data storage in the cloud This paper also deals with architectures for security and privacy management in the cloud storage environmen

Fault aware task scheduling in cloud using min-min and DBSCAN

Cloud computing leverages computing resources by managing these resources globally in a more efficient manner as compared to individual resource services. It requires us to deliver the resources in a heterogeneous environment and also in a highly dynamic nature. Hence, there is always a risk of resource allocation failure that can maximize the delay in task execution. Such adverse impact in the cloud environment also raises questions on quality of service (QoS). Resource management for cloud application and service have bigger challenges and many researchers have proposed several solutions but there is room for improvement. Clustering the resources clustering and mapping them according to task can also be an option to deal with such task failure or mismanaged resource allocation. Density-based spatial clustering of applications with noise (DBSCAN) is a stochastic approach-based algorithm which has the capability to cluster the resources in a cloud environment. The proposed algorithm considers high execution enabled powerful data centers with least fault probability during resource allocation which reduces the probability of fault and increases the tolerance. The simulation is cone using CloudsSim 5.0 tool kit. The results show 25% average improve in execution time, 6.5% improvement in number of task completed and 3.48% improvement in count of task failed as compared to ACO, PSO, BB-BC (Bib = g bang Big Crunch) and WHO(Whale optimization algorithm)

Architectural and mobility management designs in internet-based infrastructure wireless mesh networks

Wireless mesh networks (WMNs) have recently emerged to be a cost-effective solution to support large-scale wireless Internet access. They have numerous ap- plications, such as broadband Internet access, building automation, and intelligent transportation systems. One research challenge for Internet-based WMNs is to design efficient mobility management techniques for mobile users to achieve seamless roam- ing. Mobility management includes handoff management and location management. The objective of this research is to design new handoff and location management techniques for Internet-based infrastructure WMNs. Handoff management enables a wireless network to maintain active connections as mobile users move into new service areas. Previous solutions on handoff manage- ment in infrastructure WMNs mainly focus on intra-gateway mobility. New handoff issues involved in inter-gateway mobility in WMNs have not been properly addressed. Hence, a new architectural design is proposed to facilitate inter-gateway handoff man- agement in infrastructure WMNs. The proposed architecture is designed to specifi- cally address the special handoff design challenges in Internet-based WMNs. It can facilitate parallel executions of handoffs from multiple layers, in conjunction with a data caching mechanism which guarantees minimum packet loss during handoffs. Based on the proposed architecture, a Quality of Service (QoS) handoff mechanism is also proposed to achieve QoS requirements for both handoff and existing traffic before and after handoffs in the inter-gateway WMN environment. Location management in wireless networks serves the purpose of tracking mobile users and locating them prior to establishing new communications. Existing location management solutions proposed for single-hop wireless networks cannot be directly applied to Internet-based WMNs. Hence, a dynamic location management framework in Internet-based WMNs is proposed that can guarantee the location management performance and also minimize the protocol overhead. In addition, a novel resilient location area design in Internet-based WMNs is also proposed. The formation of the location areas can adapt to the changes of both paging load and service load so that the tradeoff between paging overhead and mobile device power consumption can be balanced, and at the same time, the required QoS performance of existing traffic is maintained. Therefore, together with the proposed handoff management design, efficient mobility management can be realized in Internet-based infrastructure WMNs

Dynamic QoS: Automatically Modifying QoS Queue's Maximum Bandwidth Rate-Limit of Network Devices for Network Improvement

The heterogeneous data traffic of today's network is a huge challenge to existing best-effort network technology, particularly in the context of large Ethernet, which handles hundreds to thousands of users. The existing conventional best-effort network technology is no longer efficient to handle the diversity of traffic types in the network and requires network management equipment such as Quality of Service (QOS). Usually, QOS is implemented on the gateway router. However, for better network performance and management, to guarantee high priority for sensitive traffic like video conferencing, Voice over Internet Protocol (VoIP), and streaming media within an internal network, it is nice to have QoS implemented on each router in the LAN network, starting from the access router to the gateway router. This paper is to demonstrate the effectiveness of the proposed dynamic QoS that has been developed and deployed in the LAN, purposely to provide adequate bandwidth for sensitive traffic when the network utilization is high and congested, by automatically modifying the QoS Queue's Maximum Bandwidth Rate-Limit of the best-effort traffic queue of the related router. The performance of the proposed developed dynamic QoS was evaluated via a comparison study before and after the dynamic QoS was presented in the network simulation environment that was built using Mininet. Results from the testing show that the developed dynamic QoS can improve the network's performance by automatically giving the appropriate bandwidth for sensitive traffic on the fly while needed/on demand