Testbed

About: Testbed is a research topic. Over the lifetime, 10858 publications have been published within this topic receiving 147147 citations. The topic is also known as: test bed.

Dyson: an architecture for extensible wireless LANs

Abstract: Dyson is a new software architecture for building customizable WLANs. While research in wireless networks has made great strides, these advancements have not seen the light of day in real WLAN deployments. One of the key reasons is that today's WLANs are not architected to embrace change. For example, system administrators cannot fine-tune the association policy for their particular environment: an administrator may know certain nodes in certain locations interfere with each other and cause a severe degradation in throughput, and hence, such associations must be avoided in the particular deployment. Dyson defines a set of APIs that allow clients and APs to send pertinent information such as radio channel conditions to a central controller. The central controller processes this information, to form a global view of the network. This global view, combined with historical information about spatial and temporal usage patterns, allows the central controller enact a rich set of policies to control the network's behavior. Dyson provides a Python-based scripting API that allows the central controller's policies to be extended for site-specific customizations and new optimizations that leverage historical knowledge. We have built a prototype implementation of Dyson, which currently runs on a 28-node testbed distributed across one floor of a typical academic building. Using this testbed, we examine various aspects of the architecture in detail, and demonstrate the ease of implementing a wide range of policies. Using Dyson, we demonstrate optimizing associations, handling VoIP clients, reserving airtime for specific users, and optimizing handoffs for mobile clients.

SLA-Driven Adaptive Resource Management for Web Applications on a Heterogeneous Compute Cloud

Abstract: Current service-level agreements (SLAs) offered by cloud providers make guarantees about quality attributes such as availability. However, although one of the most important quality attributes from the perspective of the users of a cloud-based Web application is its response time, current SLAs do not guarantee response time. Satisfying a maximum average response time guarantee for Web applications is difficult due to unpredictable traffic patterns, but in this paper we show how it can be accomplished through dynamic resource allocation in a virtual Web farm. We present the design and implementation of a working prototype built on a EUCALYPTUS-based heterogeneous compute cloud that actively monitors the response time of each virtual machine assigned to the farm and adaptively scales up the application to satisfy a SLA promising a specific average response time. We demonstrate the feasibility of the approach in an experimental evaluation with a testbed cloud and a synthetic workload. Adaptive resource management has the potential to increase the usability of Web applications while maximizing resource utilization.

Implementation and Evaluation of Cooperative Communication Schemes in Software-Defined Radio Testbed

Abstract: Cooperative communication is a promising technique for future wireless networks, which significantly improves link capacity and reliability by leveraging broadcast nature of wireless medium and exploiting cooperative diversity. However, most of existing works investigate its performance theoretically or by simulation. It has been widely accepted that simulations often fail to faithfully capture many real-world radio signal propagation effects, which can be overcome through developing physical wireless network testbeds. In this work, we build a cooperative testbed based on GNU Radio and Universal Software Radio Peripheral (USRP) platform, which is a promising open-source software-defined radio system. Both single-relay cooperation and multi-relay cooperation can be supported in our testbed. Some key techniques are provided to solve the main challenges during the testbed development: e.g., maximum ratio combine in single-relay transmission and synchronized transmission among multiple relays. Extensive experiments are carried out in the testbed to evaluate performance of various cooperative communication schemes. The results show that cooperative transmission achieves significant performance enhancement in terms of link reliability and end-to-end throughput.

Dynamic module deployment in a fog computing platform

Abstract: Several applications, such as smart cities, smart homes and smart hospitals adopt Internet of Things (IoT) networks to collect data from IoT devices. The incredible growing speed of the number of IoT devices congests the networks and the large amount of data, which are streamed to data centers for further analysis, overload the data centers. In this paper, we implement a fog computing platform that leverages end devices, edge networks, and data centers to serve the IoT applications. In this paper, we focus on implementing a fog computing platform, which dynamically pushes programs to the devices. The programs pushed to the devices pre-process the data before transmitting them over the Internet, which reduces the network traffic and the load of data centers. We survey the existing platforms and virtualization technologies, and leverage them to implement the fog computing platform. Moreover, we formulate a deployment problem of the programs. We propose an efficient heuristic deployment algorithm to solve the problem. We also implement an optimal algorithm for comparisons. We conduct experiments with a real testbed to evaluate our algorithms and fog computing platform. The proposed algorithm shows near-optimal performance, which only deviates from optimal algorithm by at most 2% in terms of satisfied requests. Moreover, the proposed algorithm runs in real-time, and is scalable. More precisely, it computes 1000 requests with 500 devices in < 2 seconds. Last, the implemented fog computing platform results in real-time deployment speed: it deploys 20 requests < 10 seconds.