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The energy consumption of data centers has been increasing continuously during the last years due to the rising demands of computational power especially in current Grid- and Cloud Computing systems, which directly influence the increment in operational costs as well as carbon dioxide (CO2) emission. To reduce energy consumption within the cloud data center, it required energy-aware virtual machines...
Current cloud users pay for statically configured VM sizes irrespective of usage. It is more favorable for users to consume (and be billed for) just the right amount of resources necessary to satisfy the performance requirement of their applications. We take a novel perspective to enable such resource usage, where we assume that the cloud operator exposes a small, dynamic fraction of its infrastructure,...
Recently, Cloud based Content Delivery Network (CCDN) has emerged as efficient content delivery architecture to provide content delivery services with improved Quality of Service (QoS), scalability and resource efficiency. Replica server placement is a key design issue in CCDNs and involves deciding the placement of replica servers on geographically dispersed cloud sites that minimizes the operational...
State-of-the-art emergency navigation approaches are designed to evacuate civilians during a disaster based on real-time decisions using a pre-defined algorithm and live sensory data. Hence, casualties caused by the poor decisions and guidance are only apparent at the end of the evacuation process and cannot then be remedied. Previous research shows that the performance of routing algorithms for evacuation...
Efficient energy use has become a critical issue for designing and managing of cloud data centers. Virtualization is a key technology for reducing energy cost and improving resource utilization in data centers. One of the challenges faced by virtualized data centers is to decide how to pack VMs on the least number of physical machines. This paper presents a VM management framework which is based on...
Anonymization is a common technique for publishing a location data set in a privacy-preserving way. However, such an anonymized data set lacks trajectory information of users, which could be beneficial to many location-based analytic services. In this paper, we present a dynamic pseudonym scheme for constructing alternate possible paths of mobile users to protect their location privacy. We introduce...
Internet-scale services like YouTube are provisioned by large Content Delivery Networks (CDNs), which push content as close as possible to the end-users to improve their Quality of Experience (QoE) and to pursue their own optimization goals. Adopting space and time variant traffic delivery policies, CDNs serve users' requests from multiple servers/caches at different physical locations and different...
With the widespread use of mobile devices, the location-based service (LBS) applications become increasingly popular, which introduces the new security challenge to protect user's location privacy. On one hand, a user expects to report his own location as far as possible away from his real location to protect his location privacy. On the other hand, in order to obtain high quality of service (QoS),...
Nowadays there is a high demand for security assurance within Cloud Computing world. To meet this demand, security practitioners attempt to assess security vulnerabilities that any given cloud system may have, however this task present some challenges when exposed to a complex cloud system. Different security tools have been developed to facilitate the vulnerabilities discovery process. In this paper...
Anycast communication is gaining much interest due to the deployment and the growing importance of new network services, including Content Delivery Networks (CDNs) and grid/cloud computing, among others. Concurrently, elastic optical networks (EONs), being a very promising solution for future optical transport networks, are considered as effective and cost-efficient approach for supporting such bandwidth-demanding...
This paper presents feedback control algorithms to autonomously deploy and scale multiple web applications on a given Infrastructure as a Service cloud. The proposed algorithms provide automatic deployment and undeployment of applications and proportional-derivative scaling of the application server tier. The algorithms use utilization metrics as input and do not require a performance model of the...
With the rapid advance of cloud computing, large scale data center plays a key role in cloud computing. Energy consumption of such distributed systems has become a prominent problem and received much attention. Among existing energy-saving methods, application scheduling can reduce energy consumption by replacing and consolidating applications to decrease the number of running servers. However, most...
High availability, reliability and scalability are basic prerequisites for cloud applications. Due to dynamically varying workloads, it's necessary to provide resource guarantees to cloud applications for meeting QoS requirements. However, it's not trivial to generate a precise scalability policy for multi-tiers cloud applications to adapt to dynamically varying workload and satisfy QoS requirements...
Data Grid provides geographically distributed storage resources for large-scale data-intensive applications that generate large data sets. Because data is the important resource in data grids, an efficient management is needed to minimize the response time of applications. Replication is typically used in data grids to improve access time and to reduce the bandwidth consumption. In this paper, we...
Most of previous research on survivable networks has been focused on protecting the unicast traffic against random failures. In this paper we propose a new approach, called RA (resistant-to-attack), to provide protection of anycast and unicast communications against attacks on irregular (e.g. scale-free) networks. We use the single backup path approach to provide protection against a single node failure...
On chip multiprocessors (CMPs) platforms, multiple co-scheduled applications can severely degrade performance and quality of service (QoS) when they contend for last-level cache (LLC) resources. Whether an application will impose destructive interference on co-scheduled applications is largely dependent on its own inherent cache access behavior characteristics. In this work, we first present case...
In this paper, we study the impact of tasks reallocation onto a multi-cluster environment where clusters are heterogeneous and use different resources management policies. In this context, we propose a reallocation mechanism that migrates waiting jobs from one cluster to another. We performed simulations using real traces to study benefits of reallocations. We compared two algorithms providing the...
The distributed rate limiting (DRL) paradigm is a recently proposed mechanism for decentralized control of cloud-based services. DRL is a simple and efficient approach to resolve the issues of pricing and resource control/engineering of cloud based services. The existing DRL schemes focus on very specific performance metrics (such as loss rate and fair-share) and their design heavily depends on the...
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