Marian Mihailescu

Bio: Marian Mihailescu is an academic researcher from National University of Singapore. The author has contributed to research in topics: Computer science & Resource (project management). The author has an hindex of 6, co-authored 9 publications receiving 328 citations.

Dynamic Resource Pricing on Federated Clouds

Abstract: Current large distributed systems allow users to share and trade resources. In cloud computing, users purchase different types of resources from one or more resource providers using a fixed pricing scheme. Federated clouds, a topic of recent interest, allows different cloud providers to share resources for increased scalability and reliability. However, users and providers of cloud resources are rational and maximize their own interest when consuming and contributing shared resources. In this paper, we present a dyanmic pricing scheme suitable for rational users requests containing multiple resource types. Using simulations, we compare the efficiency of our proposed strategy-proof dynamic scheme with fixed pricing, and show that user welfare and the percentage of successful requests is increased by using dynamic pricing.

On Economic and Computational-Efficient Resource Pricing in Large Distributed Systems

Abstract: There is growing interest in large-scale systems where globally distributed and commoditized resources can be shared and traded, such as peer-to-peer networks, grids, and cloud computing. Users of these systems are rational and maximize their own interest when consuming and contributing shared resources, even if by doing so they affect the overall efficiency of the system. To manage rational users, resource pricing and allocation can provide the necessary incentives for users to behave such that the overall efficiency can be maximized. In this paper, we propose a dynamic pricing mechanism for the allocation of shared resources, and evaluate its performance. In contrast with several existing trading models, our scheme is designed to allocate a request with multiple resource types, such that the user does not have to aggregate different resource types manually. We formally prove the economic properties of our pricing scheme using the mechanism design framework. We perform both theoretical and simulation analysis to evaluate the economic and computational efficiency of the allocation and the scalability of the mechanism. Our simulations are validated against a prototype implementation on PlanetLab.

Strategy-Proof dynamic resource pricing of multiple resource types on federated clouds

Abstract: There is growing interest in large-scale resource sharing with emerging architectures such as cloud computing, where globally distributed and commoditized resources can be shared and traded Federated clouds, a topic of recent interest, aims to integrate different types of cloud resources from different providers, to increase scalability and reliability In federated clouds, users are rational and maximize their own interest when consuming and contributing shared resources, while globally distributed resource supply and demand changes as users join and leave the cloud dynamically over time In this paper, we propose a dynamic pricing scheme for multiple types of shared resources in federated clouds and evaluate its performance Fixed pricing, currently used by cloud providers, does not reflect the dynamic resource price due to the changes in supply and demand Using simulations, we compare the economic and computational efficiencies of our proposed dynamic pricing scheme with fixed pricing We show that the user utility is increased, while the percentage of successful buyer requests and the percentage of allocated seller resources is higher with dynamic pricing.

A Strategy-proof Pricing Scheme for Multiple Resource Type Allocations

Abstract: Resource sharing on the Internet is becoming increasingly pervasive. Recently, there is growing interest in distributed systems such as peer-to-peer and grid, with efforts being directed towards resource allocation strategies that incentivize users to share resources. While combinatorial auctions can perform multiple resource type allocations, it is computationally a NP-complete problem. Thus, allocation in large distributed resource sharing systems focuses mainly on a single resource type. We propose a strategy-proof, VCG-based resource pricing scheme for resource allocation in dynamic markets where users behave rationally in meeting their own interest. Our mechanism is designed to meet the needs of large distributed systems, delivering the following key properties: multiple resource type allocations, individual rationality, incentive compatibility for both buyers and sellers, budget balance and computational efficiency. Simulation evaluation of our prototype based on a centralized implementation demonstrates the viability of our approach, as compared to both traditional and combinatorial auctions.

The Impact of User Rationality in Federated Clouds

Abstract: With cloud computing, the long-envisioned dream of computing as utility is achieved. Many of the current standalone cloud providers offer resources and services using pay-per-use fixed pricing. Spot pricing, recently introduced in Amazon EC2, is more efficient by setting the resource price dynamically, based on demand. However, this pricing scheme, similar to the uniform price auction, is truthful only when supply can be adjusted, such as the case of a standalone cloud provider. In a federated cloud, where resources from multiple cloud providers are integrated to increase elasticity and reliability, rational users can have a greater impact. In this paper, we evaluate the impact of rationality in a federated cloud, by comparing the consumer welfare achieved by spot pricing, currently used in Amazon EC2, and a strategy-proof pricing scheme. We consider different EC2 regions as providers in a federated cloud, and use traces of spot prices to determine the consumer requests and the user welfare. Our results show that spot pricing is not suitable in a federated cloud, where rational users can increase their welfare by being untruthful.

On Global Electricity Usage of Communication Technology: Trends to 2030

Abstract: This work presents an estimation of the global electricity usage that can be ascribed to Communication Technology (CT) between 2010 and 2030. The scope is three scenarios for use and production of consumer devices, communication networks and data centers. Three different scenarios, best, expected, and worst, are set up, which include annual numbers of sold devices, data traffic and electricity intensities/efficiencies. The most significant trend, regardless of scenario, is that the proportion of use-stage electricity by consumer devices will decrease and will be transferred to the networks and data centers. Still, it seems like wireless access networks will not be the main driver for electricity use. The analysis shows that for the worst-case scenario, CT could use as much as 51% of global electricity in 2030. This will happen if not enough improvement in electricity efficiency of wireless access networks and fixed access networks/data centers is possible. However, until 2030, globally-generated renewable electricity is likely to exceed the electricity demand of all networks and data centers. Nevertheless, the present investigation suggests, for the worst-case scenario, that CT electricity usage could contribute up to 23% of the globally released greenhouse gas emissions in 2030.

A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges

Abstract: Cloud computing with its three key facets (i.e., Infrastructure-as-a-Service, Platform-as-a-Service, and Software-as-a-Service) and its inherent advantages (e.g., elasticity and scalability) still faces several challenges. The distance between the cloud and the end devices might be an issue for latency-sensitive applications such as disaster management and content delivery applications. Service level agreements (SLAs) may also impose processing at locations where the cloud provider does not have data centers. Fog computing is a novel paradigm to address such issues. It enables provisioning resources and services outside the cloud, at the edge of the network, closer to end devices, or eventually, at locations stipulated by SLAs. Fog computing is not a substitute for cloud computing but a powerful complement. It enables processing at the edge while still offering the possibility to interact with the cloud. This paper presents a comprehensive survey on fog computing. It critically reviews the state of the art in the light of a concise set of evaluation criteria. We cover both the architectures and the algorithms that make fog systems. Challenges and research directions are also introduced. In addition, the lessons learned are reviewed and the prospects are discussed in terms of the key role fog is likely to play in emerging technologies such as tactile Internet.

A Comprehensive Survey on Fog Computing: State-of-the-art and Research Challenges

Abstract: Cloud computing with its three key facets (i.e., IaaS, PaaS, and SaaS) and its inherent advantages (e.g., elasticity and scalability) still faces several challenges. The distance between the cloud and the end devices might be an issue for latency-sensitive applications such as disaster management and content delivery applications. Service Level Agreements (SLAs) may also impose processing at locations where the cloud provider does not have data centers. Fog computing is a novel paradigm to address such issues. It enables provisioning resources and services outside the cloud, at the edge of the network, closer to end devices or eventually, at locations stipulated by SLAs. Fog computing is not a substitute for cloud computing but a powerful complement. It enables processing at the edge while still offering the possibility to interact with the cloud. This article presents a comprehensive survey on fog computing. It critically reviews the state of the art in the light of a concise set of evaluation criteria. We cover both the architectures and the algorithms that make fog systems. Challenges and research directions are also introduced. In addition, the lessons learned are reviewed and the prospects are discussed in terms of the key role fog is likely to play in emerging technologies such as Tactile Internet.

System of distributed software quality improvement

Abstract: Provided is a system for building and validating an application (including e.g., various software versions and revisions, programming languages, code segments, among other examples) without any scripting required by a system user. In one embodiment, an SDLC system is configured to construct a build and test environment, by automatically analyzing a submitted project. The build environment is configured to assemble existing user code, for example, to generate an application to test. Code building can include any one or more of code compilation, assembly, and code interpretation. The system can include a user interface provided to clients, users, and/or customer environments to facilitate user interaction and control of build and test validation. The system can accept user specification of configurations that controls the way the system runs the user's tests. The system can also provide flexible billing models for different customers.