An adaptive and efficient buffer management scheme for resource-constrained delay tolerant networks

Provisioning buffer management mechanism is especially crucial in resource-constrained delay tolerant networks (DTNs) as maximum data delivery ratio with minimum overhead is expected in highly congested environments. However, most DTN protocols do not consider resource limitations (e.g., buffer, bandwidth) and hence, results in performance degradation. To strangle and mitigate the impact of frequent buffer overflows, this paper presents an adaptive and efficient buffer management scheme called size-aware drop (SAD) that strives to improve buffer utilization and avoid unnecessary message drops. To improve data delivery ratio, SAD exactly determines the requirement based on differential of newly arrived message(s) and available space. To vacate inevitable space from a congested buffer, SAD strives to avoid redundant message drops and deliberate to pick and discard most appropriate message(s) to minimize overhead. The performance of SAD is validated through extensive simulations in realistic environments (i.e., resource-constrained and congested) with different mobility models (i.e., Random Waypoint and disaster). Simulation results demonstrate the performance supremacy of SAD in terms of delivery probability and overhead ratio besides other metrics when compared to contemporary schemes based on Epidemic (DOA and DLA) and PRoPHET (SHLI and MOFO).     

Multi‐agent‐based sharing power economy for a smart community

In this paper, a multi‐agent‐based locally administrated power distribution hub (PDH) for social welfare is proposed that optimizes energy consumption, allocation, and management of battery energy storage systems (ESSs) for a smart community. Initially, formulation regarding optimum selection of a power storage system for a home (in terms of storage capacity) is presented. Afterwards, the concept of sharing economy is inducted in the community by demonstrating PDH. PDH is composed of multiple small‐scale battery ESSs (each owned by community users), which are connected together to form a unified‐ESS. Proposed PDH offers a localized switching mechanism that takes decision of whether to buy electricity from utility or use unified‐ESS. This decision is based on the price of electricity at ‘time of use’ and ‘state of charge’ of unified‐ESS. In response to power use or share, electricity bills are created for individual smart homes by incrementing or decrementing respective submeters. There is no buying or selling of power from PDH; there is power sharing with the concept of ‘no profit, no loss’. The objective of the proposed PDH is to limit the purchase of electricity on ‘high priced’ hours from the utility. This not only benefits the utility at crucial hours but also provides effective use of power at the demand side. The proposed multi‐agent system depicts the concept of sharing power economy within a community. Finally, the proposed model is analyzed analytically, considering on‐peak, off‐peak, and mid‐level (mid‐peak) prices of a real‐time price signal during 24 h of a day. Results clearly show vital financial benefits of ‘sharing power economy’ for end users and efficient use of power within the smart community. Copyright © 2017 John Wiley & Sons, Ltd.     

A hybrid lithium‐ion battery model for system‐level analyses

We describe an advanced lithium‐ion battery model for system‐level analyses such as electric vehicle fleet simulation or distributed energy storage applications. The model combines an empirical multi‐parameter model and an artificial neural network with particular emphasis on thermal effects such as battery internal heating. The model is fast and can accurately describe constant current charging and discharging of a battery cell at a variety of ambient temperatures. Comparison to a commonly used linear kilowatt‐hour counter battery model indicates that a linear model overestimates the usable capacity of a battery at low temperatures. We highlight the importance of including internal heating in a battery model at low temperatures, as more capacity is available when internal heating is taken into account. Copyright © 2016 John Wiley & Sons, Ltd.     

Integrated design of diesel hydrotreating processes

This work presents an integrated approach for the design of diesel hydrotreating processes employing a simulated annealing optimisation algorithm. The modelling of reactor, separation and heat recovery system for diesel hydrotreating processes is discussed, and a novel optimisation framework is developed for the design of complex refinery processes. A comparison with conventional approach to process design, i.e. sequential evolution of design, is given to illustrate the ability of proposed approach to obtain overall hydrotreating process designs with minimum total annualised costs. The proposed integrated approach takes into account the trade-offs between capital and operating costs, as well as interactions between the hydrotreater, distillation column, and the associated heat exchanger network.     

A decision support framework for metrics selection in goal-based measurement programs: GQM-DSFMS

Software organizations face challenges in managing and sustaining their measurement programs over time. The complexity of measurement programs increase with exploding number of goals and metrics to collect. At the same time, organizations usually have limited budget and resources for metrics collection. It has been recognized for quite a while that there is the need for prioritizing goals, which then ought to drive the selection of metrics. On the other hand, the dynamic nature of the organizations requires measurement programs to adapt to the changes in the stakeholders, their goals, information needs and priorities. Therefore, it is crucial for organizations to use structured approaches that provide transparency, traceability and guidance in choosing an optimum set of metrics that would address the highest priority information needs considering limited resources. This paper proposes a decision support framework for metrics selection (DSFMS) which is built upon the widely used Goal Question Metric (GQM) approach. The core of the framework includes an iterative goal-based metrics selection process incorporating decision making mechanisms in metrics selection, a pre-defined Attributes/Metrics Repository, and a Traceability Model among GQM elements. We also discuss alternative prioritization and optimization techniques for organizations to tailor the framework according to their needs. The evaluation of the GQM-DSFMS framework was done through a case study in a CMMI Level 3 software company.     

Prediction of Dry Powder Inhaler Formulation Performance From Surface Energetics and Blending Dynamics

The purpose of these studies was to investigate the ability of surface energy measurements and rates of mixing in dry powder inhaler (DPI) formulations to predict aerosol dispersion performance. Two lactose carrier systems comprising either spray-dried or milled particles were developed such that they had identical physical characteristics except for surface morphology and surface energies avoiding confounding variables common in other studies. Surface energy measurements confirmed significant differences between the powder systems. Spray-dried lactose had a higher surface entropy (0.20 vs. 0.13 mJ/m²K) and surface enthalpy (103.2 vs. 79.2 mJ/m²) compared with milled lactose. Mixing rates of budesonide or fluorescein were assessed dynamically, and significant differences in blending were observed between lactose systems for both drugs. Surface energies of the lactose carriers were inversely proportional to dispersion performance. In addition, the root mean square (RMS) of blending rates correlated positively with aerosol dispersion performance. Both techniques have potential utility in routine screening of DPI formulations.     

Embedded passive components in advanced 3D chips and micro/nano electronic systems

Microsystem Technologies - Electronic devices are shrinking day by day, while the speed and reliability is increasing. At the same time, IC designs and micro/nano electronic systems are becoming...     

Toward the modeling of data provenance in scientific publications

In this paper, we implement a provenance-aware system for documenting publications, called PADS. It employs a three-layered provenance hierarchy, which can output diverse types of provenance data related to the research life cycle. From this, we generate different profiles for research ventures, reviewers, and authors. PADS employs the standard Open Provenance Model (OPM) specification for capturing provenance data, and stores this data as ontological instances. We show that data is retrieved without any apparent delay in the execution time of the queries. We also demonstrate how this data can be used to make useful recommendations to the organizers, in order to manage upcoming research ventures.     

Effect of polyacrylic acid (PAA) binder system on particle orientation during dry-pressing

Effect of polyacrylic acid (PAA) binder system on the development of particle orientation during uniaxial pressing is reported. Granules of different properties were compacted using uniaxial pressing at various pressure and their degree of particle orientation (DPO) was determined. The increment trend of DPO varies with granule strength and shows higher value for binder system of higher flexibility. Anisotropic shrinkage related to particle orientation is shown by compact of higher relative density (RD) and DPO; whereas anisotropic shrinkage related to non-uniform packing density is shown by compact of lower RD and DPO. Anisotropic shrinkage remains in the former compact while isotropic shrinkage was obtained for the latter compact at sintering temperature of 1600 °C. Subsequent cold isostatic pressing increases DPO and sintering shrinkage ratio of uniaxially pressed compacts.