Using Dedicated and Opportunistic Networks in Synergy for a Cost-effective Distributed Stream Processing Platform

This paper presents a case for exploiting the synergy of dedicated and opportunistic network resources in a distributed hosting platform for data stream processing applications. Our previous studies have demonstrated the benefits of combining dedicated reliable resources with opportunistic resources in case of high-throughput computing applications, where timely allocation of the processing units is the primary concern. Since distributed stream processing applications demand large volume of data transmission between the processing sites at a consistent rate, adequate control over the network resources is important here to assure a steady flow of processing. In this paper, we propose a system model for the hybrid hosting platform where stream processing servers installed at distributed sites are interconnected with a combination of dedicated links and public Internet. Decentralized algorithms have been developed for allocation of the two classes of network resources among the competing tasks with an objective towards higher task throughput and better utilization of expensive dedicated resources. Results from extensive simulation study show that with proper management, systems exploiting the synergy of dedicated and opportunistic resources yield considerably higher task throughput and thus, higher return on investment over the systems solely using expensive dedicated resources.Comment: 9 page

Efficient memory management in video on demand servers

In this article we present, analyse and evaluate a new memory management technique for video-on-demand servers. Our proposal, Memory Reservation Per Storage Device (MRPSD), relies on the allocation of a fixed, small number of memory buffers per storage device. Selecting adequate scheduling algorithms, information storage strategies and admission control mechanisms, we demonstrate that MRPSD is suited for the deterministic service of variable bit rate streams to intolerant clients. MRPSD allows large memory savings compared to traditional memory management techniques, based on the allocation of a certain amount of memory per client served, without a significant performance penaltyPublicad

Device-Centric Cooperation in Mobile Networks

The increasing popularity of applications such as video streaming in today's mobile devices introduces higher demand for throughput, and puts a strain especially on cellular links. Cooperation among mobile devices by exploiting both cellular and local area connections is a promising approach to meet the increasing demand. In this paper, we consider that a group of cooperative mobile devices, exploiting both cellular and local area links and within proximity of each other, are interested in the same video content. Traditional network control algorithms introduce high overhead and delay in this setup as the network control and cooperation decisions are made in a source-centric manner. Instead, we develop a device-centric stochastic cooperation scheme. Our device-centric scheme; DcC allows mobile devices to make control decisions such as flow control, scheduling, and cooperation without loss of optimality. Thanks to being device-centric, DcC reduces; (i) overhead; i.e., the number of control packets that should be transmitted over cellular links, so cellular links are used more efficiently, and (ii) the amount of delay that each packet experiences, which improves quality of service. The simulation results demonstrate the benefits of DcC

MorphoSys: efficient colocation of QoS-constrained workloads in the cloud

In hosting environments such as IaaS clouds, desirable application performance is usually guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated for unencumbered use for proper operation. Arbitrary colocation of applications with different SLAs on a single host may result in inefficient utilization of the host’s resources. In this paper, we propose that periodic resource allocation and consumption models -- often used to characterize real-time workloads -- be used for a more granular expression of SLAs. Our proposed SLA model has the salient feature that it exposes flexibilities that enable the infrastructure provider to safely transform SLAs from one form to another for the purpose of achieving more efficient colocation. Towards that goal, we present MORPHOSYS: a framework for a service that allows the manipulation of SLAs to enable efficient colocation of arbitrary workloads in a dynamic setting. We present results from extensive trace-driven simulations of colocated Video-on-Demand servers in a cloud setting. These results show that potentially-significant reduction in wasted resources (by as much as 60%) are possible using MORPHOSYS.National Science Foundation (0720604, 0735974, 0820138, 0952145, 1012798

Power Management Techniques for Data Centers: A Survey

With growing use of internet and exponential growth in amount of data to be stored and processed (known as 'big data'), the size of data centers has greatly increased. This, however, has resulted in significant increase in the power consumption of the data centers. For this reason, managing power consumption of data centers has become essential. In this paper, we highlight the need of achieving energy efficiency in data centers and survey several recent architectural techniques designed for power management of data centers. We also present a classification of these techniques based on their characteristics. This paper aims to provide insights into the techniques for improving energy efficiency of data centers and encourage the designers to invent novel solutions for managing the large power dissipation of data centers.Comment: Keywords: Data Centers, Power Management, Low-power Design, Energy Efficiency, Green Computing, DVFS, Server Consolidatio