Multi-capacity bin packing with dependent items and its application to the packing of brokered workloads in virtualized environments

Providing resource allocation with performance predictability guarantees is increasingly important in cloud platforms, especially for data-intensive applications, in which performance depends greatly on the available rates of data transfer between the various computing/storage hosts underlying the virtualized resources assigned to the application. Existing resource allocation solutions either assume that applications manage their data transfer between their virtualized resources, or that cloud providers manage their internal networking resources. With the increased prevalence of brokerage services in cloud platforms, there is a need for resource allocation solutions that provides predictability guarantees in settings, in which neither application scheduling nor cloud provider resources can be managed/controlled by the broker. This paper addresses this problem, as we define the Network-Constrained Packing (NCP) problem of finding the optimal mapping of brokered resources to applications with guaranteed performance predictability. We prove that NCP is NP-hard, and we define two special instances of the problem, for which exact solutions can be found efficiently. We develop a greedy heuristic to solve the general instance of the NCP problem , and we evaluate its efficiency using simulations on various application workloads, and network models.This work was done while author was at Boston University. It was partially supported by NSF CISE awards #1430145, #1414119, #1239021 and #1012798. (1430145 - NSF CISE; 1414119 - NSF CISE; 1239021 - NSF CISE; 1012798 - NSF CISE

Energy management in communication networks: a journey through modelling and optimization glasses

The widespread proliferation of Internet and wireless applications has produced a significant increase of ICT energy footprint. As a response, in the last five years, significant efforts have been undertaken to include energy-awareness into network management. Several green networking frameworks have been proposed by carefully managing the network routing and the power state of network devices. Even though approaches proposed differ based on network technologies and sleep modes of nodes and interfaces, they all aim at tailoring the active network resources to the varying traffic needs in order to minimize energy consumption. From a modeling point of view, this has several commonalities with classical network design and routing problems, even if with different objectives and in a dynamic context. With most researchers focused on addressing the complex and crucial technological aspects of green networking schemes, there has been so far little attention on understanding the modeling similarities and differences of proposed solutions. This paper fills the gap surveying the literature with optimization modeling glasses, following a tutorial approach that guides through the different components of the models with a unified symbolism. A detailed classification of the previous work based on the modeling issues included is also proposed

Recent Advances in Graph Partitioning

We survey recent trends in practical algorithms for balanced graph partitioning together with applications and future research directions

Design of a Scalable Path Service for the Internet

Despite the world-changing success of the Internet, shortcomings in its routing and forwarding system have become increasingly apparent. One symptom is an escalating tension between users and providers over the control of routing and forwarding of packets: providers understandably want to control use of their infrastructure, and users understandably want paths with sufficient quality-of-service (QoS) to improve the performance of their applications. As a result, users resort to various “hacks” such as sending traffic through intermediate end-systems, and the providers fight back with mechanisms to inspect and block such traffic. To enable users and providers to jointly control routing and forwarding policies, recent research has considered various architectural approaches in which provider- level route determination occurs separately from forwarding. With this separation, provider-level path computation and selection can be provided as a centralized service: users (or their applications) send path queries to a path service to obtain provider- level paths that meet their application-specific QoS requirements. At the same time, providers can control the use of their infrastructure by dictating how packets are forwarded across their network. The separation of routing and forwarding offers many advantages, but also brings a number of challenges such as scalability. In particular, the path service must respond to path queries in a timely manner and periodically collect topology information containing load-dependent (i.e., performance) routing information. We present a new design for a path service that makes use of expensive pre- computations, parallel on-demand computations on performance information, and caching of recently computed paths to achieve scalability. We demonstrate that, us- ing commodity hardware with a modest amount of resources, the path service can respond to path queries with acceptable latency under a realistic workload. The ser- vice can scale to arbitrarily large topologies through parallelism. Finally, we describe how to utilize the path service in the current Internet with existing Internet applica- tions

Ab initio computations of molecular systems by the auxiliary-field quantum Monte Carlo method

The auxiliary-field quantum Monte Carlo (AFQMC) method provides a computational framework for solving the time-independent Schroedinger equation in atoms, molecules, solids, and a variety of model systems. AFQMC has recently witnessed remarkable growth, especially as a tool for electronic structure computations in real materials. The method has demonstrated excellent accuracy across a variety of correlated electron systems. Taking the form of stochastic evolution in a manifold of non-orthogonal Slater determinants, the method resembles an ensemble of density-functional theory (DFT) calculations in the presence of fluctuating external potentials. Its computational cost scales as a low-power of system size, similar to the corresponding independent-electron calculations. Highly efficient and intrinsically parallel, AFQMC is able to take full advantage of contemporary high-performance computing platforms and numerical libraries. In this review, we provide a self-contained introduction to the exact and constrained variants of AFQMC, with emphasis on its applications to the electronic structure in molecular systems. Representative results are presented, and theoretical foundations and implementation details of the method are discussed.Comment: 22 pages, 11 figure