Hermann de Meer

Energy-Efficient Cloud Computing

Energy efficiency is increasingly important for future information and communication technologies (ICT), because the increased usage of ICT, together with increasing energy costs and the need to reduce green house gas emissions call for energy-efficient technologies that decrease the overall energy consumption of computation, storage and communications. Cloud computing has recently received considerable attention, as a promising approach for delivering ICT services by improving the utilization of data centre resources. In principle, cloud computing can be an inherently energy-efficient technology for ICT provided that its potential for significant energy savings that have so far focused on hardware aspects, can be fully explored with respect to system operation and networking aspects. Thus this paper, in the context of cloud computing, reviews the usage of methods and technologies currently used for energy-efficient operation of computer hardware and network infrastructure. After surveying some of the current best practice and relevant literature in this area, this paper identifies some of the remaining key research challenges that arise when such energy-saving techniques are extended for use in cloud computing environments.

A survey of programmable networks

In this paper we present a programmable networking model that provides a common framework for understanding the state-of-the-art in programmable networks. A number of projects are reviewed and discussed against a set of programmable network characteristics. We believe that a number of important innovations are creating a paradigm shift in networking leading to higher levels of network programmability. These innovations include the separation between transmission hardware and control software, availability of open programmable network interfaces, accelerated virtualization of networking infrastructure, rapid creation and deployment of new network services and environments for resource partitioning and coexistence of multiple distinct network architectures. We present a simple qualitative comparison of the surveyed work and make a number of observations about the direction of the field.

Review: Dynamic key management in wireless sensor networks: A survey

Wireless sensor networks (WSNs) have a vast field of applications, including environment monitoring, battlefield surveillance and target tracking systems. As WSNs are usually deployed in remote or even hostile environments and sensor nodes are prone to node compromise attacks, the adoption of dynamic key management is extremely important. However, the resource-constrained nature of sensor nodes hinders the use of dynamic key management solutions designed for wired and ad hoc networks. Hence, many dynamic key management schemes have been proposed for WSNs recently. This paper investigates the special requirements of dynamic key management in sensor network environments, and introduces several basic evaluation metrics. In this work, the state of the art dynamic key management schemes are classified into different groups and summarized based on the evaluation metrics. Finally, several possible future research directions for dynamic key management are provided.

Evaluating and modeling power consumption of multi-core processors

Recently, energy-efficient computing has become a major interest, both in the mobile and IT sectors. With the advent of multi-core processors and their energy-saving mechanisms, there is a necessity to model their power consumption. The existing models for multi-core processors are based on the assumption that the power consumption of multiple cores performing parallel computations is equal to the sum of the power of each of those active cores. In this paper, we analyze this assumption and show that it leads to lack of accuracy when applied to modern processors such as quad-core. Based on our analysis, we present a methodology for estimating the power consumption of multi-core processors. Unlike existing models, we take into account resource sharing and power saving mechanisms. We show that our approach provides an accuracy within a maximum error of 5%.

Scalable service deployment on software-defined networks

It is widely accepted that the network of the future will require a greater degree of service awareness and optimal use of network resources. This article presents an architectural design for an open software-defined network infrastructure that enables the composition of fast and guaranteed services in an efficient manner and the execution of these services in an adaptive way, taking into account better shared network resources provided by network virtualization. Validation results are provided with special emphasis on service deployment scalability over virtualized network infrastructures.

Optimal mapping of virtual networks with hidden hops

Network virtualization has emerged as a solution for the Internet inability to address the required challenges caused by the lack of coordination among Internet service providers for the deployment of new services. The allocation of resources is one of the main problems in network virtualization, mainly in the mapping of virtual nodes and links to specific substrate nodes and paths, also known as the virtual network embedding problem. This paper proposes an algorithm based on optimization theory, to map the virtual links and nodes requiring a specific demand, looking for the maximization of the spare bandwidth and spare CPU in the substrate network, taking into account the CPU demanded by the hidden hops when a virtual link is mapped. The components of the virtual networks (nodes and links) that do not ask for an specific demand are then allocated following a fairness criteria.

idMesh: graph-based disambiguation of linked data

We tackle the problem of disambiguating entities on the Web. We propose a user-driven scheme where graphs of entities -- represented by globally identifiable declarative artifacts -- self-organize in a dynamic and probabilistic manner. Our solution has the following two desirable properties: i) it lets end-users freely define associations between arbitrary entities and ii) it probabilistically infers entity relationships based on uncertain links using constraint-satisfaction mechanisms. We outline the interface between our scheme and the current data Web, and show how higher-layer applications can take advantage of our approach to enhance search and update of information relating to online entities. We describe a decentralized infrastructure supporting efficient and scalable entity disambiguation and demonstrate the practicability of our approach in a deployment over several hundreds of machines.

Performance tradeoffs of energy-aware virtual machine consolidation

Increasing power consumption of IT infrastructures and growing electricity prices have led to the development of several energy-saving techniques in the last couple of years. Virtualization and consolidation of services is one of the key technologies in data centers to reduce overprovisioning and therefore increase energy savings. This paper shows that the energy-optimal allocation of virtualized services in a heterogeneous server infrastructure is NP-hard and can be modeled as a variant of the multidimensional vector packing problem. Furthermore, it proposes a model to predict the performance degradation of a service when it is consolidated with other services. The model allows considering the tradeoff between power consumption and service performance during service allocation. Finally, the paper presents two heuristics that approximate the energy-optimal and performance-aware resource allocation problem and shows that the allocations determined by the proposed heuristics are more energy-efficient than the widely applied maximum-density consolidation.

A methodology to predict the power consumption of servers in data centres

Until recently, there have been relatively few studies exploring the power consumption of ICT resources in data centres. In this paper, we propose a methodology to capture the behaviour of most relevant energy-related ICT resources in data centres and present a generic model for them. This is achieved by decomposing the design process into four modelling phases. Furthermore, unlike the state-of-the-art approaches, we provide detailed power consumption models at server and storage levels. We evaluate our model for different types of servers and show that it suffers from an error rate of 2% in the best case, and less than 10% in the worst case.

ALEVIN - A Framework to Develop, Compare, and Analyze Virtual Network Embedding Algorithms

Network virtualization is recognized as an enabling technology for the Future Internet. Applying virtualization of network resources leads to the problem of mapping virtual resources to physical resources, known as “Virtual Network Embedding” (VNE). Several algorithms attempting to solve this problem have been discussed in the literature, so far. However, comparison of VNE algorithms is hard, as each algorithm focuses on different criteria. To that end, we introduce a framework to compare different algorithms according to a set of metrics, which allow to evaluate the algorithms and compute their results on a given scenario for arbitrary parameters.