Real-Time Data Processing With Lambda Architecture

Data has evolved immensely in recent years, in type, volume and velocity. There are several frameworks to handle the big data applications. The project focuses on the Lambda Architecture proposed by Marz and its application to obtain real-time data processing. The architecture is a solution that unites the benefits of the batch and stream processing techniques. Data can be historically processed with high precision and involved algorithms without loss of short-term information, alerts and insights. Lambda Architecture has an ability to serve a wide range of use cases and workloads that withstands hardware and human mistakes. The layered architecture enhances loose coupling and flexibility in the system. This a huge benefit that allows understanding the trade-offs and application of various tools and technologies across the layers. There has been an advancement in the approach of building the LA due to improvements in the underlying tools. The project demonstrates a simplified architecture for the LA that is maintainable

Biological Assessments of Six Selected Fishes, Amphibians, and Mussels in Illinois

ID: 8758; issued November 1, 1996INHS Technical Report prepared for Illinois Department of Natural Resources, Division of Natural Heritag

Streams of events and performance of queuing systems: The basic anatomy of arrival/departure processes, when focus is set on autocorrelation

Judging from the vast number of articles in the field of queuing simulation, that assumes i.i.d. in one or more of the stochastic processes used to model the situation at hand, often without much validation, it seems that sequence independence must be a very basic property of many real life situation or at least a very sound approximation. However, on the other hand, most actual decision making is based upon information taken from the past - where else! In fact the only real alternative that comes into my mind is to let a pair of dices fully and completely rule behaviour, but I wonder if such a decision setup is that widespread in consequent use anywhere. So, how come that sequence independence is so relatively popular in describing real system processes? I can only think of three possible explanations to this dilemma - (1) either sequence dependence is present, but is mostly not of a very significant nature or (2) aggregate system behaviour is in general very different from just the summing-up (even for finite sets of micro-behavioural patterns) and/or (3) it is simply a wrong assumption that in many cases is chosen by mere convention or plain convenience. It is evident that before choosing some arrival processes for some simulation study a thorough preliminary analysis has to be undertaken in order to uncover the basic time series nature of the interacting processes. Flexible methods for generating streams of autocorrelated variates of any desired distributional type, such as the ARTA method or some autocorrelation extended descriptive sampling method, can then easily be applied. The results from the Livny, Melamed and Tsiolis (1993) study as well as the results from this work both indicates that system performance measures as for instance average waiting time or average time in system are significantly influenced by the taken i.i.d. versus the autocorrelations assumptions. Plus/minus 35% in performance, but most likely a worsening, is easily observed, when comparing even moderate (probably more realistic) autocorrelation assumptions with the traditionally and commonly used i.i.d. assumptions.Autocorrelation; queuing systems; TES method; ARTA method Descriptive/Selective sampling; Simulation; Job/flow-shop; performance; control

Orchestrating Service Migration for Low Power MEC-Enabled IoT Devices

Multi-Access Edge Computing (MEC) is a key enabling technology for Fifth Generation (5G) mobile networks. MEC facilitates distributed cloud computing capabilities and information technology service environment for applications and services at the edges of mobile networks. This architectural modification serves to reduce congestion, latency, and improve the performance of such edge colocated applications and devices. In this paper, we demonstrate how reactive service migration can be orchestrated for low-power MEC-enabled Internet of Things (IoT) devices. Here, we use open-source Kubernetes as container orchestration system. Our demo is based on traditional client-server system from user equipment (UE) over Long Term Evolution (LTE) to the MEC server. As the use case scenario, we post-process live video received over web real-time communication (WebRTC). Next, we integrate orchestration by Kubernetes with S1 handovers, demonstrating MEC-based software defined network (SDN). Now, edge applications may reactively follow the UE within the radio access network (RAN), expediting low-latency. The collected data is used to analyze the benefits of the low-power MEC-enabled IoT device scheme, in which end-to-end (E2E) latency and power requirements of the UE are improved. We further discuss the challenges of implementing such schemes and future research directions therein

Plant height and hydraulic vulnerability to drought and cold

Understanding how plants survive drought and cold is increasingly important as plants worldwide experience dieback with drought in moist places and grow taller with warming in cold ones. Crucial in plant climate adaptation are the diameters of water-transporting conduits. Sampling 537 species across climate zones dominated by angiosperms, we find that plant size is unambiguously the main driver of conduit diameter variation. And because taller plants have wider conduits, and wider conduits within species are more vulnerable to conduction-blocking embolisms, taller conspecifics should be more vulnerable than shorter ones, a prediction we confirm with a plantation experiment. As a result, maximum plant size should be short under drought and cold, which cause embolism, or increase if these pressures relax. That conduit diameter and embolism vulnerability are inseparably related to plant size helps explain why factors that interact with conduit diameter, such as drought or warming, are altering plant heights worldwide

Deformable Nanovesicles Synthesized through an Adaptable Microfluidic Platform for Enhanced Localized Transdermal Drug Delivery.

Phospholipid-based deformable nanovesicles (DNVs) that have flexibility in shape offer an adaptable and facile method to encapsulate diverse classes of therapeutics and facilitate localized transdermal delivery while minimizing systemic exposure. Here we report the use of a microfluidic reactor for the synthesis of DNVs and show that alteration of input parameters such as flow speeds as well as molar and flow rate ratios increases entrapment efficiency of drugs and allows fine-tuning of DNV size, elasticity, and surface charge. To determine the ability of DNV-encapsulated drug to be delivered transdermally to a local site, we synthesized, characterized, and tested DNVs carrying the fluorescently labeled hydrophilic bisphosphonate drug AF-647 zoledronate (AF647-Zol). AF647-Zol DNVs were lyophilized, resuspended, and applied topically as a paste to the calvarial skin of mice. High-resolution fluorescent imaging and confocal microscopy revealed significant increase of encapsulated payload delivery to the target tissue-cranial bone-by DNVs as compared to nondeformable nanovesicles (NVs) or aqueous drug solutions. Interestingly, NV delivery was not superior to aqueous drug solution. Our studies show that microfluidic reactor-synthesized DNVs can be produced in good yield, with high encapsulation efficiency, reproducibility, and stability after storage, and represent a useful vehicle for localized transdermal drug delivery