Data Serialization Formats for the Internet of Things

IoT devices rely on data exchange with gateways and cloud servers. However, the performance of today's serialization formats and libraries on embedded systems with energy and memory constraints is not well-documented and hard to predict. We evaluate (de)serialization and transmission cost of mqtt.eclipse.org payloads on 8- to 32-bit microcontrollers and find that Protocol Buffers (as implemented by NanoPB) and the XDR format, dating back to 1987, are most efficient

Energy-Efficient GPS-Based Positioning in the Android Operating System

We present our ongoing collaborative work on EnDroid, an energy-efficient GPS-based positioning system for the Android Operating System. EnDroid is based on the EnTracked positioning system, developed at the University of Aarhus, Denmark. We describe the current prototypical state of our implementation and present our experiences and conclusions from preliminarily evaluating EnDroid on the Google Nexus One Smartphone. Although the preliminary results seem to support the approach, there are still several open questions, both at the application interface, as well as at the hardware management level

mxkernel: a novel system software stack for data processing on modern hardware

Emerging hardware platforms are characterized by large degrees of parallelism, complex memory hierarchies, and increasing hardware heterogeneity. Their theoretical peak data processing performance can only be unleashed if the different pieces of systems software collaborate much more closely and if their traditional dependencies and interfaces are redesigned. We have developed the key concepts and a prototype implementation of a novel system software stack named mxkernel. For MxKernel, efficient large scale data processing capabilities are a primary design goal. To achieve this, heterogeneity and parallelism become first-class citizens and deep memory hierarchies are considered from the very beginning. Instead of a classical “thread” model, mxkernel provides a simpler control flow abstraction: mxtasks model closed units of work, for which mxkernel will guarantee the required execution semantics, such exclusive access to a specific object in memory. They can be a very elegant abstraction also for heterogeneity and resource sharing. Furthermore, mxtasks are annotated with metadata, such as code variants (to support heterogeneity), memory access behavior (to improve cache efficiency and support memory hierarchies), or dependencies between mxtasks (to improve scheduling and avoid synchronization cost). With precisely the required metadata available, mxkernel can provide a lightweight, yet highly efficient form of resource management, even across applications, operating system, and database. Based on the mxkernel prototype we present preliminary results from this ambitious undertaking. We argue that threads are an ill-suited control flow abstraction for our modern computer architectures and that a task-based execution model is to be favored

PhyNetLab: An IoT-Based Warehouse Testbed

Future warehouses will be made of modular embedded entities with communication ability and energy aware operation attached to the traditional materials handling and warehousing objects. This advancement is mainly to fulfill the flexibility and scalability needs of the emerging warehouses. However, it leads to a new layer of complexity during development and evaluation of such systems due to the multidisciplinarity in logistics, embedded systems, and wireless communications. Although each discipline provides theoretical approaches and simulations for these tasks, many issues are often discovered in a real deployment of the full system. In this paper we introduce PhyNetLab as a real scale warehouse testbed made of cyber physical objects (PhyNodes) developed for this type of application. The presented platform provides a possibility to check the industrial requirement of an IoT-based warehouse in addition to the typical wireless sensor networks tests. We describe the hardware and software components of the nodes in addition to the overall structure of the testbed. Finally, we will demonstrate the advantages of the testbed by evaluating the performance of the ETSI compliant radio channel access procedure for an IoT warehouse

Evaluation of SLA-based decision strategies for VM scheduling in cloud data centers

Copyright © 2016 held by owner/author(s). Service level agreements (SLAs) gain more and more importance in the area of cloud computing. An SLA is a contract between a customer and a cloud service provider (CSP) in which the CSP guarantees functional and non-functional quality of service parameters for cloud services. Since CSPs have to pay for the hardware used as well as penalties for violating SLAs, they are eager to fulfill these agreements while at the same time optimizing the utilization of their resources. In this paper we examine SLA-aware VM scheduling strategies for cloud data centers. The service level objectives considered are resource usage and availability. The sample resources are CPU and RAM. They can be overprovisioned by the CSPs which is the main leverage to increase their revenue. The availability of a VM is affected by migrating it within and between data centers. To get realistic results, we simulate the effect of the strategies using the FederatedCloudSim framework and real-world workload traces of business-critical VMs. Our evaluation shows that there are considerable differences between the scheduling strategies in terms of SLA violations and the number of migrations. From all strategies considered, the combination of the Minimization of Migrations strategy for VM selection and the Worst Fit strategy for host selection achieves the best results

Integrating the common variability language with multilanguage annotations for web engineering

Web applications development involves managing a high diversity of files and resources like code, pages or style sheets, implemented in different languages. To deal with the automatic generation of custom-made configurations of web applications, industry usually adopts annotation-based approaches even though the majority of studies encourage the use of composition-based approaches to implement Software Product Lines. Recent work tries to combine both approaches to get the complementary benefits. However, technological companies are reticent to adopt new development paradigms such as feature-oriented programming or aspect-oriented programming. Moreover, it is extremely difficult, or even impossible, to apply these programming models to web applications, mainly because of their multilingual nature, since their development involves multiple types of source code (Java, Groovy, JavaScript), templates (HTML, Markdown, XML), style sheet files (CSS and its variants, such as SCSS), and other files (JSON, YML, shell scripts). We propose to use the Common Variability Language as a composition-based approach and integrate annotations to manage fine grained variability of a Software Product Line for web applications. In this paper, we (i) show that existing composition and annotation-based approaches, including some well-known combinations, are not appropriate to model and implement the variability of web applications; and (ii) present a combined approach that effectively integrates annotations into a composition-based approach for web applications. We implement our approach and show its applicability with an industrial real-world system.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Towards Adjusting Mobile Devices To User's Behaviour

Mobile devices are a special class of resource-constrained em- bedded devices. Computing power, memory, the available energy, and network bandwidth are often severely limited. These constrained re- sources require extensive optimization of a mobile system compared to larger systems. Any needless operation has to be avoided. Time- consuming operations have to be started early on. For instance, load- ing files ideally starts before the user wants to access the file. So-called prefetching strategies optimize system’s operation. Our goal is to ad- just such strategies on the basis of logged system data. Optimization is then achieved by predicting an application’s behavior based on facts learned from earlier runs on the same system. In this paper, we ana- lyze system-calls on operating system level and compare two paradigms, namely server-based and device-based learning. The results could be used to optimize the runtime behaviour of mobile devices

Financial evaluation of SLA-based VM scheduling strategies for cloud federations

In recent years, cloud federations have gained popularity. Small as well as big cloud service providers (CSPs) join federations to reduce their costs, and also cloud management software like OpenStack offers support for federations. In a federation, individual CSPs cooperate such that they can move load to partner clouds at high peaks and possibly offer a wider range of services to their customers. Research in this area addresses the organization of such federations and strategies that CSPs can apply to increase their profit. In this paper we present the latest extensions to the FederatedCloudSim framework that considerably improve the simulation and evaluation of cloud federations. These simulations include service-level agreements (SLAs), scheduling and brokering strategies on various levels, the use of real-world cloud workload traces and a fine-grained financial evaluation using the new CloudAccount module. We use FederatedCloudSim to compare scheduling and brokering strategies on the federation level. Among them are new strategies that conduct auctions or consult a reliance factor to select an appropriate federated partner for running outsourced virtual machines. Our results show that choosing the right strategy has a significant impact on SLA compliance and revenue

RAMpage: Graceful Degradation Management for Memory Errors in Commodity Linux Servers

Abstract—Memory errors are a major source of reliability problems in current computers. Undetected errors may result in program termination, or, even worse, silent data corruption. Recent studies have shown that the frequency of permanent memory errors is an order of magnitude higher than previously assumed and regularly affects everyday operation. Often, neither additional circuitry to support hardware-based error detection nor downtime for performing hardware tests can be afforded. In the case of permanent memory errors, a system faces two challenges: detecting errors as early as possible and handling them while avoiding system downtime. To increase system reliability, we have developed RAMpage, an online memory testing infrastructure for commodity x86-64-based Linux servers, which is capable of efficiently detecting memory errors and which provides graceful degradation by withdrawing affected memory pages from further use. We describe the design and implementation of RAMpage and present results of an extensive qualitative as well as quantitative evaluation. Keywords-Fault tolerance, DRAM chips, Operating systems I